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

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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

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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,

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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,

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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,

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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,

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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

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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

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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

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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

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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

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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,

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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,

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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

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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

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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,

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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,

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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

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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,

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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,

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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

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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,

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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,

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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,

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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,

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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

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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,

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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

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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

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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,

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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

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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

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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,

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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

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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

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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

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

Reference 49

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

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

Reference 51

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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

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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

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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

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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

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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

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

Reference 57

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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

Reference 86

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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

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

Reference 88

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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