Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T20:41:25.310895Z
Paper Citation Record · LEDGER
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking
As of 21 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2505.12340.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
45 of 45 outbound references displayed
- verified exact0
- verified fuzzy43
- unresolved2
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation bc2baee1-f8a5-46d7-9c5f-ded1bf04b7bb · outbound
This paper cites Cubature Kalman filters.IEEE Transactions on Automatic Control, 54(6): 1254–1269, 2009.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Cubature Kalman filters.IEEE Transactions on Automatic Control, 54(6): 1254–1269, 2009
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.946401Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 18461092-b287-4f78-bae4-04ee7cc730e7 · outbound
This paper cites Recurrent Kalman networks: Factorized inference in high-dimensional deep feature spaces.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Recurrent Kalman networks: Factorized inference in high-dimensional deep feature spaces
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.935749Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation f77a3d24-db2a-45dc-bdb3-6ca48b69bfc9 · outbound
This paper cites XGBoost: A scalable tree boosting system.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking XGBoost: A scalable tree boosting system
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.925569Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c4a6b534-df2b-4c92-84b3-f07dd6c86119 · outbound
This paper cites Split-KalmanNet: A robust model-based deep learning approach for state estimation.IEEE Transac- tions on Vehicular Technology, 72(9):12326–12331, 2023.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Split-KalmanNet: A robust model-based deep learning approach for state estimation.IEEE Transac- tions on Vehicular Technology, 72(9):12326–12331, 2023
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.913977Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 2e2437cd-93e1-4225-be5b-ef9c2df96445 · outbound
This paper cites Long short-term memory Kalman filters: Recurrent neural estimators for pose regu- larization.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Long short-term memory Kalman filters: Recurrent neural estimators for pose regu- larization
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.900860Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 43a8fe87-a206-4e9b-a8a0-02d4402b87d0 · outbound
This paper cites Normalizing Kalman filters for multi- variate time series analysis.Advances in Neural Information Processing Systems (NeurIPS), 33:2995–3007, 2020.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Normalizing Kalman filters for multi- variate time series analysis.Advances in Neural Information Processing Systems (NeurIPS), 33:2995–3007, 2020
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.887416Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 03942d0e-824e-48f8-bd6d-115aa3ed1dfe · outbound
This paper cites Improved IMM al- gorithm based on RNNs.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Improved IMM al- gorithm based on RNNs
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.874386Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c813e94b-9959-446c-b839-7a7904538335 · outbound
This paper cites Self-supervised 6D object pose estimation for robot manipulation.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Self-supervised 6D object pose estimation for robot manipulation
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.862367Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c6e133cc-37c1-46dd-be17-797339662b71 · outbound
This paper cites A disentangled recognition and nonlinear dynam- ics model for unsupervised learning.Advances in Neural Information Processing Systems (NeurIPS), 30, 2017.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking A disentangled recognition and nonlinear dynam- ics model for unsupervised learning.Advances in Neural Information Processing Systems (NeurIPS), 30, 2017
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.847567Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 64656b6a-fb2b-4860-9caa-98ef6f337fe1 · outbound
This paper cites Addressing function approximation error in actor-critic methods.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Addressing function approximation error in actor-critic methods
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.836683Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 69393d57-1b4d-45a7-8f5f-21b6a39f25dc · outbound
This paper cites RL-AKF: An adaptive Kalman filter navigation algorithm based on re- inforcement learning for ground vehicles.Remote Sensing, 12(11):1704, 2020.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking RL-AKF: An adaptive Kalman filter navigation algorithm based on re- inforcement learning for ground vehicles.Remote Sensing, 12(11):1704, 2020
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.824860Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 55d718c0-449f-42b8-84a9-1724b9490da9 · outbound
This paper cites DANSE: Data-driven non-linear state estimation of model- free process in unsupervised learning setup.IEEE Transac- tions on Signal Processing, 2024.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking DANSE: Data-driven non-linear state estimation of model- free process in unsupervised learning setup.IEEE Transac- tions on Signal Processing, 2024
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.813542Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 77478e33-5dab-4f43-8c43-81a4cee29277 · outbound
This paper cites Dynamical Variational Autoencoders: A Comprehensive Review.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Dynamical Variational Autoencoders: A Comprehensive Review
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:41:25.192324Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cdd3e093-786f-4bc3-aae9-c78f72c712fa · outbound
This paper cites Opti- mization or architecture: How to hack Kalman filtering.Ad- vances in Neural Information Processing Systems (NeurIPS), 36, 2024.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Opti- mization or architecture: How to hack Kalman filtering.Ad- vances in Neural Information Processing Systems (NeurIPS), 36, 2024
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.802316Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 29684d0b-88ae-4d24-a5a1-9e9d3def11c8 · outbound
This paper cites Long short-term memory.Neural Computation MIT-Press, 1997.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Long short-term memory.Neural Computation MIT-Press, 1997
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.789359Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 58e37be3-0838-4a9d-8430-a11d95c1991e · outbound
This paper cites Multiple pedestrian tracking from monocular videos in an interacting multiple model framework.IEEE Transactions on Image Processing, 27(3):1361–1375, 2017.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Multiple pedestrian tracking from monocular videos in an interacting multiple model framework.IEEE Transactions on Image Processing, 27(3):1361–1375, 2017
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.776801Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation fea48a76-1005-4248-9232-9f57a664cfa8 · outbound
This paper cites Design and comparison of mode-set adaptive IMM algorithms for ma- neuvering target tracking.IEEE Transactions on Aerospace and Electronic Systems, 35(1):343–350, 1999.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Design and comparison of mode-set adaptive IMM algorithms for ma- neuvering target tracking.IEEE Transactions on Aerospace and Electronic Systems, 35(1):343–350, 1999
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.762266Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 76d76448-c4cc-4f8b-a93e-0005495eb3d0 · outbound
This paper cites The new trend of state esti- mation: From model-driven to hybrid-driven methods.Sen- sors, 21(6):2085, 2021.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking The new trend of state esti- mation: From model-driven to hybrid-driven methods.Sen- sors, 21(6):2085, 2021
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.743563Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 985300c5-5079-417c-bbc7-c9ef66dcc028 · outbound
This paper cites Sampled-Data State Estimation for LSTM.IEEE Transactions on Neural Networks and Learn- ing Systems, 2024.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Sampled-Data State Estimation for LSTM.IEEE Transactions on Neural Networks and Learn- ing Systems, 2024
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.731951Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a7916f9e-b50d-4f14-96cb-08721410cc92 · outbound
This paper cites A new approach to linear filtering and prediction problems.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking A new approach to linear filtering and prediction problems
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.721510Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 30b0b2f5-72fc-4822-9c95-7b6963ecc964 · outbound
This paper cites Structured inference networks for nonlinear state space models.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Structured inference networks for nonlinear state space models
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.710900Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 4e0e10cf-d0e2-4e57-9281-4d4a4316f682 · outbound
This paper cites Improved IMM algorithm based on XGBoost.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Improved IMM algorithm based on XGBoost
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.700270Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 18b35f1c-6068-4588-b0b5-54e115c4e74f · outbound
This paper cites Time3D: End-to-end joint monocu- lar 3D object detection and tracking for autonomous driving.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Time3D: End-to-end joint monocu- lar 3D object detection and tracking for autonomous driving
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.688548Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation ff239b80-5f9f-4fde-9229-ba26b7da44b8 · outbound
This paper cites Hierarchical model-based human motion track- ing via unscented Kalman filter.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Hierarchical model-based human motion track- ing via unscented Kalman filter
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.676927Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation ed2485cf-2c53-415e-8c00-be5246e64d33 · outbound
This paper cites Exploring simple 3D multi-object tracking for autonomous driving.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Exploring simple 3D multi-object tracking for autonomous driving
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.664869Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 51826d9a-8445-4437-bede-ab7ec4c6f3dd · outbound
This paper cites Interacting multiple model methods in target track- ing: a survey.IEEE Transactions on Aerospace and Elec- tronic Systems, 34(1):103–123, 1998.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Interacting multiple model methods in target track- ing: a survey.IEEE Transactions on Aerospace and Elec- tronic Systems, 34(1):103–123, 1998
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.650809Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 42499362-b05d-4daf-a01b-e5f02e6fae29 · outbound
This paper cites Recurrent neural net- works.Design and Applications, 5(64-67):2, 2001.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Recurrent neural net- works.Design and Applications, 5(64-67):2, 2001
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.634127Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 9a608e38-2b9e-4f95-87f7-56d17fe5c684 · outbound
This paper cites Modeling and estimation for tracking maneuvering targets.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Modeling and estimation for tracking maneuvering targets
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.623450Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation ea63a8f1-a7a9-4ebe-b4ff-44fdc9610366 · outbound
This paper cites P2b: Point-to-box network for 3D object tracking in point clouds.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking P2b: Point-to-box network for 3D object tracking in point clouds
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.609274Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 8de46f4c-802d-47a2-a8c4-1bc8fcb0f767 · outbound
This paper cites Optimization-based state es- timation: Current status and some new results.Journal of Process Control, 22(8):1439–1444, 2012.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Optimization-based state es- timation: Current status and some new results.Journal of Process Control, 22(8):1439–1444, 2012
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.595258Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c9f01281-6c7d-4738-b83b-4968786799fc · outbound
This paper cites Unsupervised learned Kalman filtering.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Unsupervised learned Kalman filtering
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.578376Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation df07bb8e-1383-4869-bad2-7c38516c5bd7 · outbound
This paper cites KalmanNet: Neural network aided Kalman filtering for partially known dynamics.IEEE Transactions on Signal Processing, 70: 1532–1547, 2022.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking KalmanNet: Neural network aided Kalman filtering for partially known dynamics.IEEE Transactions on Signal Processing, 70: 1532–1547, 2022
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.559145Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b14bf3f1-0e06-49fb-8f67-e2dd41c8357f · outbound
This paper cites Kalman and extended Kalman filters: Concept, derivation and properties.Institute for Systems and Robotics, 43(46):3736–3741, 2004.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Kalman and extended Kalman filters: Concept, derivation and properties.Institute for Systems and Robotics, 43(46):3736–3741, 2004
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.547081Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 9c688498-f555-4955-bf4a-0b61e014c748 · outbound
This paper cites Algorithm for perfor- mance analysis of the imm algorithm.IEEE Transactions on Aerospace and Electronic Systems, 47(2):1114–1124, 2011.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Algorithm for perfor- mance analysis of the imm algorithm.IEEE Transactions on Aerospace and Electronic Systems, 47(2):1114–1124, 2011
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.525305Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 9e48b2a3-8af6-48e3-bc59-4c5dce765db8 · outbound
This paper cites Gaussian processes for machine learn- ing.International Journal of Neural Systems, 14(02):69– 106, 2004.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Gaussian processes for machine learn- ing.International Journal of Neural Systems, 14(02):69– 106, 2004
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.512704Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation aeece236-c69e-40b5-bad1-406f4e76b0e9 · outbound
This paper cites Incorporating Transformer and LSTM to Kalman Filter with EM algorithm for state estimation.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Incorporating Transformer and LSTM to Kalman Filter with EM algorithm for state estimation
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:41:25.277165Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 63fe968d-8d66-4093-88ee-16cae9b9c855 · outbound
This paper cites Model-based deep learning.Proceedings of the IEEE, 111(5):465–499, 2023.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Model-based deep learning.Proceedings of the IEEE, 111(5):465–499, 2023
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.500082Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c939b7f0-3987-4a17-a84e-467d19aab17f · outbound
This paper cites Re- inforcement learning compensated extended Kalman filter for attitude estimation.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Re- inforcement learning compensated extended Kalman filter for attitude estimation
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.488238Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation fa97a948-2abd-42de-a979-05e47de51b3c · outbound
This paper cites Attention is all you need.Advances in Neural Information Processing Systems (NeurIPS), 2017.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Attention is all you need.Advances in Neural Information Processing Systems (NeurIPS), 2017
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.476126Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation ce87f137-f34f-455a-9efd-dcc852d3fe24 · outbound
This paper cites Edge comput- ing enabled video segmentation for real-time traffic monitor- ing in internet of vehicles.Pattern Recognition, 121:108146,.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Edge comput- ing enabled video segmentation for real-time traffic monitor- ing in internet of vehicles.Pattern Recognition, 121:108146,
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.460625Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation f13d8e70-d039-4200-a045-46fb9814598d · outbound
This paper cites Online selecting discriminative tracking features using particle filter.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Online selecting discriminative tracking features using particle filter
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.444051Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 810f216b-c6ce-49df-9342-7778ae9dff88 · outbound
This paper cites Center- based 3D object detection and tracking.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Center- based 3D object detection and tracking
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.430755Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation fd71a966-4d23-4696-9233-d252e608614a · outbound
This paper cites Privacy-preserving push-sum distributed cubature informa- tion filter for nonlinear target tracking with switching di- rected topologies.ISA Transactions, 136:16–30, 2023.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Privacy-preserving push-sum distributed cubature informa- tion filter for nonlinear target tracking with switching di- rected topologies.ISA Transactions, 136:16–30, 2023
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.419575Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 08519342-034f-47e2-8a60-191c3d080a96 · outbound
This paper cites Diffusion-based filter for fast and accurate collabora- tive tracking with low data transmission.Authorea Preprints,.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Diffusion-based filter for fast and accurate collabora- tive tracking with low data transmission.Authorea Preprints,
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.408566Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 08aef0e1-8610-4b7c-afc1-a22304759635 · outbound
This paper cites Innovative interaction ap- proach in IMM filtering for vehicle motion models with un- equal states dimension.IEEE Transactions on Vehicular Technology, 71(4):3579–3594, 2022.
DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Innovative interaction ap- proach in IMM filtering for vehicle motion models with un- equal states dimension.IEEE Transactions on Vehicular Technology, 71(4):3579–3594, 2022
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:41:25.395662Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Pith citing papers
No inbound Pith citation observations are available.