Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities | Paper Citation Record

Observation ec4c3803-1c51-4897-aae5-03f556c0321b · outbound

This paper cites Joint optimization of radar and communications performance in 6G cellular sys- tems,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Joint optimization of radar and communications performance in 6G cellular sys- tems,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.281065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68ec9627-e1f8-4d49-acc2-50a6fec607d0 · outbound

This paper cites Op- timized precoders for massive MIMO OFDM dual radar-communication systems,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Op- timized precoders for massive MIMO OFDM dual radar-communication systems,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.286419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19d7190a-a96e-4a08-a8f4-58a9ed760a01 · outbound

This paper cites An overview of signal processing techniques for joint communication and radar sensing,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities An overview of signal processing techniques for joint communication and radar sensing,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.290853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de4c6852-5e93-484e-a569-a18656c99a99 · outbound

This paper cites A survey on fundamental limits of integrated sensing and communication,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities A survey on fundamental limits of integrated sensing and communication,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.295472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4783762d-3d24-4140-bd9e-a4a55c3a3780 · outbound

This paper cites Integrated sensing and communication waveform design: A sur- vey,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Integrated sensing and communication waveform design: A sur- vey,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.300364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfd62cdc-cda6-4f7b-ada5-0b6d33bfd213 · outbound

This paper cites Integrated sensing and communication signals toward 5G-A and 6G: a survey,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Integrated sensing and communication signals toward 5G-A and 6G: a survey,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.304907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c6a186c-ad9f-442a-a7f8-1a9b9e4f7140 · outbound

This paper cites Integrated sensing and communication: Enabling techniques, applications, tools and data sets, standardization, and future di- rections,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Integrated sensing and communication: Enabling techniques, applications, tools and data sets, standardization, and future di- rections,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.310368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45168db0-726d-4a6e-8425-cfa2953fae9c · outbound

This paper cites Integrated sensing and communication with recon- figurable intelligent surfaces: Opportunities, applica- tions, and future directions,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Integrated sensing and communication with recon- figurable intelligent surfaces: Opportunities, applica- tions, and future directions,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.314859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea75e63d-9912-4a90-8791-031d27f6196e · outbound

This paper cites Integrated sensing and com- munications: Recent advances and ten open chal- lenges,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Integrated sensing and com- munications: Recent advances and ten open chal- lenges,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.319003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19b007a0-a0af-48de-84b9-a6f7b38e340d · outbound

This paper cites A survey on machine learning enhanced integrated sensing and communication systems: Architectures, algorithms, and applications,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities A survey on machine learning enhanced integrated sensing and communication systems: Architectures, algorithms, and applications,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.323513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd5cd5d5-2634-48c1-ba1e-c49440cf7761 · outbound

This paper cites Integrated sensing and communication for 6G: Ten key machine learning roles,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Integrated sensing and communication for 6G: Ten key machine learning roles,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.327633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc982719-3000-4e64-a2e4-447131042192 · outbound

This paper cites Machine learning for wireless communications in the internet of things: A compre- hensive survey,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Machine learning for wireless communications in the internet of things: A compre- hensive survey,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.331748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8afb193-2f0b-487f-932b-fb5100fa2a36 · outbound

This paper cites Machine learning for 6G wireless networks: Car- rying forward enhanced bandwidth, massive access, 25 and ultrareliable/low-latency service,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Machine learning for 6G wireless networks: Car- rying forward enhanced bandwidth, massive access, 25 and ultrareliable/low-latency service,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.335963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7b0d58d-a0f4-4f86-9c43-a6ac4e4f6b5c · outbound

This paper cites Applications of deep reinforcement learning in communications and networking: A survey,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Applications of deep reinforcement learning in communications and networking: A survey,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.340176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7599791-8171-44d2-b615-d69444937a8f · outbound

This paper cites Deep learning in mobile and wireless networking: A survey,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Deep learning in mobile and wireless networking: A survey,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.344329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d82ddc19-f33a-491e-b112-92f5e5e3f94d · outbound

This paper cites Distributed machine learning for wireless communi- cation networks: Techniques, architectures, and appli- cations,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Distributed machine learning for wireless communi- cation networks: Techniques, architectures, and appli- cations,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.348499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 051f156f-3c6b-4664-a067-ac8195787a3f · outbound

This paper cites Machine learning meets communication networks: Current trends and future challenges,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Machine learning meets communication networks: Current trends and future challenges,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.352754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55e477fb-3bc4-482c-ba47-a479c838b6a9 · outbound

This paper cites Deep learning based communication over the air,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Deep learning based communication over the air,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.357429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c03add7-c090-4821-b9ef-e09bdaf733ab · outbound

This paper cites From distributed machine learning to feder- ated learning: A survey,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities From distributed machine learning to feder- ated learning: A survey,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.361804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f33016c7-e477-4fa3-af83-100b6e566ec2 · outbound

This paper cites Model-based on- line learning for active ISAC waveform optimization,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Model-based on- line learning for active ISAC waveform optimization,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.366211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83538efb-8e56-4642-b337-5c82ba209a10 · outbound

This paper cites Model-free online learning for waveform opti- mization in integrated sensing and communications,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Model-free online learning for waveform opti- mization in integrated sensing and communications,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.370320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5eb06295-877d-4351-be6f-5fc66e314878 · outbound

This paper cites End-to-End Learning for SLP-Based ISAC Systems.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities End-to-End Learning for SLP-Based ISAC Systems

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-05T17:02:45.482748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 424adf96-6748-476c-8f1b-05e31d33e958 · outbound

This paper cites Learning-based joint waveform optimization and receiver design for dual-functional MIMO radar and communications,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Learning-based joint waveform optimization and receiver design for dual-functional MIMO radar and communications,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.379560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b91a585-3ec0-48e1-8515-47b3fcefa67a · outbound

This paper cites End- to-end learning for integrated sensing and communi- cation,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities End- to-end learning for integrated sensing and communi- cation,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.384063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ba558fe-c84b-4862-94fe-188fc67b639a · outbound

This paper cites Re- configurable beamforming for automotive radar sens- ing and communication: A deep reinforcement learn- ing approach,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Re- configurable beamforming for automotive radar sens- ing and communication: A deep reinforcement learn- ing approach,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.388411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc9753c5-43de-40b9-b2bb-fae946c2a9fb · outbound

This paper cites Distributed unsupervised learning for inter- ference management in integrated sensing and com- munication systems,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Distributed unsupervised learning for inter- ference management in integrated sensing and com- munication systems,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.392793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 273cb4c3-b9dd-48c5-b9c7-23c3bf476f8f · outbound

This paper cites Unsupervised learning- based low-complexity integrated sensing and commu- nication precoder design,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Unsupervised learning- based low-complexity integrated sensing and commu- nication precoder design,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.397156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09b7f8e9-b12b-4015-9600-63775139a26d · outbound

This paper cites Learning-based predictive beamforming for integrated sensing and communication in vehicular networks,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Learning-based predictive beamforming for integrated sensing and communication in vehicular networks,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.401406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57ab912d-3e00-4b6e-92f0-dd18cf495832 · outbound

This paper cites Deep clstm for predictive beamforming in inte- grated sensing and communication-enabled vehicular networks,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Deep clstm for predictive beamforming in inte- grated sensing and communication-enabled vehicular networks,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.405586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb60d18d-5409-45f9-827c-40d3cdbe5f5b · outbound

This paper cites Predictive beamforming for integrated sens- ing and communication in vehicular networks: A deep learning approach,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Predictive beamforming for integrated sens- ing and communication in vehicular networks: A deep learning approach,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.409779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 985c48ce-af09-404d-b500-1d56397f0005 · outbound

This paper cites Transformer-based predictive beamforming for inte- grated sensing and communication in vehicular net- works,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Transformer-based predictive beamforming for inte- grated sensing and communication in vehicular net- works,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.414393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation caf2afb0-8340-4b30-9a6b-7115e4873efd · outbound

This paper cites Intelligent predictive beamforming for in- tegrated sensing and communication based vehicular- to-infrastructure systems,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Intelligent predictive beamforming for in- tegrated sensing and communication based vehicular- to-infrastructure systems,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.418453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21599218-233a-4333-9e0a-b5055c25ebe3 · outbound

This paper cites Integrated sensing and communications towards proactive beam- forming in mmWave V2I via multi-modal feature fu- sion (mmff),.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Integrated sensing and communications towards proactive beam- forming in mmWave V2I via multi-modal feature fu- sion (mmff),

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.422700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c45b720-2059-4ccc-8c96-70b3b888e0fc · outbound

This paper cites Predictive beamforming for vehicles with complex be- haviors in ISAC systems: A deep learning approach,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Predictive beamforming for vehicles with complex be- haviors in ISAC systems: A deep learning approach,

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.427257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c06006c6-0d3d-4544-91a4-e20f295d1ebd · outbound

This paper cites Integrated sensing and communication- enabled predictive beamforming with deep learning in vehicular networks,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Integrated sensing and communication- enabled predictive beamforming with deep learning in vehicular networks,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.432590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 742a4aa7-f87d-46df-8b27-858b4200d6c8 · outbound

This paper cites Deep-learning-based channel estimation for IRS- assisted ISAC system,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Deep-learning-based channel estimation for IRS- assisted ISAC system,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.436973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9bd95a66-3f93-45d7-9686-372f08c3a501 · outbound

This paper cites Deep-learning channel estimation for IRS- assisted integrated sensing and communication sys- tem,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Deep-learning channel estimation for IRS- assisted integrated sensing and communication sys- tem,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.441312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52eb1afe-8446-49a5-8f39-acd2aeecb0de · outbound

This paper cites Enhanced channel estimation for OTFS-assisted ISAC in vehicular networks: A deep learning ap- proach,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Enhanced channel estimation for OTFS-assisted ISAC in vehicular networks: A deep learning ap- proach,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.445414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 728739b9-3f7a-4dc4-9ac0-40fc5c7ebf44 · outbound

This paper cites Extreme learning machine-based channel estimation in IRS-assisted multi-user ISAC system,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Extreme learning machine-based channel estimation in IRS-assisted multi-user ISAC system,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.450078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85082a1e-857d-4b80-9568-0ae4ce357c2c · outbound

This paper cites Sensing integrated DFT-spread OFDM waveform and deep learning-powered receiver design for terahertz inte- grated sensing and communication systems,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Sensing integrated DFT-spread OFDM waveform and deep learning-powered receiver design for terahertz inte- grated sensing and communication systems,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.454490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5909e56c-9d87-4371-8385-593283e71c43 · outbound

This paper cites Neu- romorphic Integrated Sensing and Communications,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Neu- romorphic Integrated Sensing and Communications,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.458732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f088dd3f-2df8-4d67-9fe6-b95260bda0f4 · outbound

This paper cites Deep learning based detection for communications systems with radar in- terference,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Deep learning based detection for communications systems with radar in- terference,

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.463366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3d0679c-149b-42b0-b894-959d4e52ef26 · outbound

This paper cites ISAC receiver design: A learning-based two-stage joint data-and- target parameter estimation,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities ISAC receiver design: A learning-based two-stage joint data-and- target parameter estimation,

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.468590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77455de8-4767-4713-9ee0-32a502c52927 · outbound

This paper cites ISAC-NET: model-driven deep learning for integrated passive sensing and communication,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities ISAC-NET: model-driven deep learning for integrated passive sensing and communication,

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.473102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 873859fb-2851-424d-8fb9-43a00c0135ce · outbound

This paper cites Toward 5G NR High-Precision Indoor Positioning via Channel Fre- quency Response: A New Paradigm and Dataset Gen- eration Method,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Toward 5G NR High-Precision Indoor Positioning via Channel Fre- quency Response: A New Paradigm and Dataset Gen- eration Method,

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.477396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6cc1c83-0cf8-4d1e-8e34-fec99c6ec01b · outbound

This paper cites AutoQML: Automated Quantum Machine Learning for Wi-Fi In- tegrated Sensing and Communications,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities AutoQML: Automated Quantum Machine Learning for Wi-Fi In- tegrated Sensing and Communications,

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.482001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0d85a95-ca41-4075-bec4-eed8bbfb3a87 · outbound

This paper cites Deep Learning-aided Robust Integrated Sensing and Communications with OTFS and Superimposed Training,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Deep Learning-aided Robust Integrated Sensing and Communications with OTFS and Superimposed Training,

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.486261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8473a4dc-8433-4707-9a6f-a26922923fa1 · outbound

This paper cites Vertical Federated Edge Learning With Distributed Integrated Sensing and Communication,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Vertical Federated Edge Learning With Distributed Integrated Sensing and Communication,

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.490730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b08cb26b-9ad5-4a50-b7e0-fbeb71d6c273 · outbound

This paper cites Deep learning,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Deep learning,

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.495422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50a2b1d6-576b-4d31-bc0b-1011b3058044 · outbound

This paper cites Su- pervised learning,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Su- pervised learning,

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.500343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8a8e8b9-1ab3-4bc7-af7a-977ea2515ae5 · outbound

This paper cites Supervised learn- ing algorithms,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Supervised learn- ing algorithms,

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.505036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd71765a-6b7c-4376-9aa2-bd2c6b3c6718 · outbound

This paper cites Su- pervised machine learning: a brief primer,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Su- pervised machine learning: a brief primer,

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.510385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77aa297d-669d-452b-8a84-fb9bc73c7adc · outbound

This paper cites An empirical comparison of supervised learning algorithms,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities An empirical comparison of supervised learning algorithms,

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.515465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11b092f5-38c8-4ac6-8219-3a61eb0f6795 · outbound

This paper cites Recent ad- vances on loss functions in deep learning for computer vision,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Recent ad- vances on loss functions in deep learning for computer vision,

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.520629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67996379-858b-46f3-acd0-5eedd793f71e · outbound

This paper cites Text data augmentation for deep learning,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Text data augmentation for deep learning,

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.525300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0369384c-b5f0-4bb2-a01e-f0289db0d7b9 · outbound

This paper cites The art of data aug- mentation,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities The art of data aug- mentation,

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.530030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 171317e6-bad1-4d84-9256-840f697cb8c7 · outbound

This paper cites Ghahramani, Unsupervised Learning.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Ghahramani, Unsupervised Learning

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.535351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08789fdf-11c9-46a8-a0d2-40ba26de0d16 · outbound

This paper cites Unsu- pervised learning for parametric optimization,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Unsu- pervised learning for parametric optimization,

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.540726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14378c39-0094-436e-ad3c-8562f2e1371e · outbound

This paper cites Unsupervised deep gener- ative adversarial hashing network,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Unsupervised deep gener- ative adversarial hashing network,

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.546316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ca1b094-2529-4c8b-bd20-38d729c11dc8 · outbound

This paper cites Model-free unsuper- vised learning for optimization problems with con- straints,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Model-free unsuper- vised learning for optimization problems with con- straints,

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.550919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 412f3bee-e2d5-4891-a3fa-ce87a434851a · outbound

This paper cites Unsupervised learning for joint beamforming design in RIS-Aided ISAC systems,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Unsupervised learning for joint beamforming design in RIS-Aided ISAC systems,

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.555704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 310fae55-9701-4310-a0de-efd1f15ce5d3 · outbound

This paper cites Optimizing wireless systems using unsupervised and reinforced- unsupervised deep learning,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Optimizing wireless systems using unsupervised and reinforced- unsupervised deep learning,

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.560777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44682e8b-68cd-4167-8131-4d5a5992adc5 · outbound

This paper cites A survey on semi-supervised learning,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities A survey on semi-supervised learning,

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.565955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6aa3660-c762-4a90-b99d-8dfde4e99bf1 · outbound

This paper cites ARC: Automotive radar consistency regularization for semi-supervised learning,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities ARC: Automotive radar consistency regularization for semi-supervised learning,

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.570688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7bd75d65-4336-4c26-be44-b5b66a2beb0a · outbound

This paper cites Semi- supervised end-to-end learning for integrated sensing and communications,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Semi- supervised end-to-end learning for integrated sensing and communications,

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.575346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4181c2ee-af1d-407d-8111-c8a162b3da01 · outbound

This paper cites A survey on deep semi-supervised learning,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities A survey on deep semi-supervised learning,

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.580525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c395581-2428-488c-8bee-6fcc1c0048e0 · outbound

This paper cites Semi- supervised and unsupervised deep visual learning: A survey,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Semi- supervised and unsupervised deep visual learning: A survey,

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.585319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0f7934c-2d74-476d-aa2b-ccb3ef8835c9 · outbound

This paper cites Temporal Ensembling for Semi-Supervised Learning.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Temporal Ensembling for Semi-Supervised Learning

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.589755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 436ebb02-d0ed-43df-bdc7-1716a172565d · outbound

This paper cites Realistic evaluation of deep semi- supervised learning algorithms,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Realistic evaluation of deep semi- supervised learning algorithms,

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.594480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20037ca7-c631-4062-8ea7-cc84ae2af065 · outbound

This paper cites Reinforcement learning: A survey,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Reinforcement learning: A survey,

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.599171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a763f63-b9e8-4e59-8bfa-4c99f0f42ac7 · outbound

This paper cites A survey of deep learning applications to au- tonomous vehicle control,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities A survey of deep learning applications to au- tonomous vehicle control,

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.603826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9456633a-074d-4200-89fc-237902f0e397 · outbound

This paper cites An introduction to reinforcement learning theory: Value function methods,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities An introduction to reinforcement learning theory: Value function methods,

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.608174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32c07c7a-3f17-49d5-8b5e-94fea2825d36 · outbound

This paper cites Deep reinforcement learning: A brief survey,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Deep reinforcement learning: A brief survey,

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.613110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f0828d2-d3e3-468b-8d89-1df6b4aebd28 · outbound

This paper cites Single and multi-agent deep reinforcement learning for AI-enabled wireless networks: A tutorial,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Single and multi-agent deep reinforcement learning for AI-enabled wireless networks: A tutorial,

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.617873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c3399ba-3220-49b1-9128-81dd4cf45a60 · outbound

This paper cites Deep rein- forcement learning for autonomous driving: A survey,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Deep rein- forcement learning for autonomous driving: A survey,

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.622023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea9e4728-aad2-4222-a4d5-62f6d1ca3a49 · outbound

This paper cites Analysis and performance evaluation of transfer learning algorithms for 6G wireless networks,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Analysis and performance evaluation of transfer learning algorithms for 6G wireless networks,

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.626428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba8f471a-eca4-488e-8a58-5b83e57085a0 · outbound

This paper cites A joint energy and la- tency framework for transfer learning over 5g indus- trial edge networks,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities A joint energy and la- tency framework for transfer learning over 5g indus- trial edge networks,

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.630735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be9dbd31-fb9b-41e1-b582-1b332df93d0a · outbound

This paper cites Safe and accelerated deep reinforcement learning- based o-ran slicing: A hybrid transfer learning ap- proach,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Safe and accelerated deep reinforcement learning- based o-ran slicing: A hybrid transfer learning ap- proach,

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.635440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b3d04b0-fb58-489c-9cb7-c137fc45e46e · outbound

This paper cites Transfer learning for disruptive 5g-enabled industrial internet of things,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Transfer learning for disruptive 5g-enabled industrial internet of things,

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.639996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 871be010-0d4a-4a7c-9057-f1d28c929739 · outbound

This paper cites A transfer learning approach for compressed sensing in 6G-IoT,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities A transfer learning approach for compressed sensing in 6G-IoT,

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.644597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10f3af03-3515-4435-a4ac-e2c1f754e865 · outbound

This paper cites A survey on dis- tributed machine learning,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities A survey on dis- tributed machine learning,

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.648996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 088230e7-7e52-4e92-bb5f-53a7d44cf5fe · outbound

This paper cites Strategies and principles of distributed machine learning on big data,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Strategies and principles of distributed machine learning on big data,

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.653623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a878a0db-cf8f-4290-bb12-43b8aad66af5 · outbound

This paper cites A survey on federated learning: The journey from centralized to distributed on-site learning and beyond,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities A survey on federated learning: The journey from centralized to distributed on-site learning and beyond,

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.658207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f1ae2bd-5c95-45aa-912f-d67fcf57ed43 · outbound

This paper cites Distributed learning in wireless networks: Recent progress and future chal- lenges,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Distributed learning in wireless networks: Recent progress and future chal- lenges,

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.662759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6efafbd-4255-4052-9bb2-452e173a1747 · outbound

This paper cites Deep learning modelling techniques: current progress, applications, advantages, and chal- lenges,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Deep learning modelling techniques: current progress, applications, advantages, and chal- lenges,

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.667384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 969e192b-3a33-4f62-a215-823f8efe57fe · outbound

This paper cites Goodfellow, Y.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Goodfellow, Y

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.671765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3984bc6-2283-4830-9640-a4f0b0d1b8cb · outbound

This paper cites Deep learning for wireless communications: An emerging interdisciplinary paradigm,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Deep learning for wireless communications: An emerging interdisciplinary paradigm,

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.676420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e87c68df-f107-42cc-b733-989c9b52b820 · outbound

This paper cites Model-based deep learning,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Model-based deep learning,

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.680947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e7ab216-deca-4321-8b66-006c5ab812b6 · outbound

This paper cites Scalable deep learning on distributed infrastructures: Challenges, techniques, and tools,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Scalable deep learning on distributed infrastructures: Challenges, techniques, and tools,

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.685581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a058078-7195-4e0a-811b-69ffcea02c8f · outbound

This paper cites Complexity- driven model compression for resource-constrained deep learning on edge,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Complexity- driven model compression for resource-constrained deep learning on edge,

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.690241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f63893d-3857-40d3-8697-b3243f840f32 · outbound

This paper cites Rethinking resource management in edge learning: A joint pre-training and fine-tuning design paradigm,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Rethinking resource management in edge learning: A joint pre-training and fine-tuning design paradigm,

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.694774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d41e4bb8-b1e1-46cf-8d95-ef3f81172e7a · outbound

This paper cites Deep learning for wireless communi- cations,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Deep learning for wireless communi- cations,

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.699591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55eac6ee-3964-449f-8f41-87caa0a429ee · outbound

This paper cites Deep learning-aided 6G wireless networks: A comprehensive survey of revolutionary PHY archi- tectures,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Deep learning-aided 6G wireless networks: A comprehensive survey of revolutionary PHY archi- tectures,

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.703854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 686a824a-bc77-4873-bb33-e08c72af5257 · outbound

This paper cites Convolutional, long short-term memory, fully con- nected deep neural networks,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Convolutional, long short-term memory, fully con- nected deep neural networks,

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.708437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation faeb91e1-a579-4473-9634-019e988d5815 · outbound

This paper cites Two-stage channel estimation using convolutional neural networks for IRS-assisted mmWave systems,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Two-stage channel estimation using convolutional neural networks for IRS-assisted mmWave systems,

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.713007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d27cf978-c85c-4a79-bd9b-a41fbabab7e6 · outbound

This paper cites Deep- learning for radar: A survey,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Deep- learning for radar: A survey,

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.717512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eabae9bc-baba-4f48-963e-99dbb8f3b05e · outbound

This paper cites A sur- vey on the application of recurrent neural networks to statistical language modeling,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities A sur- vey on the application of recurrent neural networks to statistical language modeling,

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.721951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e6550b3-1492-4dc9-97c6-bd82a7d4fb6c · outbound

This paper cites From feed- forward to recurrent LSTM neural networks for lan- guage modeling,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities From feed- forward to recurrent LSTM neural networks for lan- guage modeling,

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.726405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd9b072e-850c-4130-91c8-7a17021e6c27 · outbound

This paper cites A review of re- current neural networks: LSTM cells and network ar- chitectures,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities A review of re- current neural networks: LSTM cells and network ar- chitectures,

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.731350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7b57f64-b6c1-4a52-9ce0-14edc88183a5 · outbound

This paper cites Chan- nel estimation using CNN-LSTM in RIS-NOMA as- sisted 6G network,.

Deep Learning-based Techniques for Integrated Sensing and Communication Systems: State-of-the-Art, Challenges, and Opportunities Chan- nel estimation using CNN-LSTM in RIS-NOMA as- sisted 6G network,

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:44.737633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers