Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving | Paper Citation Record

Observation 5767f0a9-5de7-4933-9d36-479c1b696c56 · outbound

This paper cites Looking at vehicles on the road: A survey of vision-based vehicle detection, tracking, and behav- ior analysis,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Looking at vehicles on the road: A survey of vision-based vehicle detection, tracking, and behav- ior analysis,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.718098Z

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Observation 3b970467-acf5-4555-9dff-56c0582c9d10 · outbound

This paper cites Deep track- ing in the wild: End-to-end tracking u sing recurrent neural networks,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Deep track- ing in the wild: End-to-end tracking u sing recurrent neural networks,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.707418Z

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Observation c20be184-5791-41bf-a7d8-49f3f8fd9b39 · outbound

This paper cites Vehicle state estimation based on min- imum model error criterion combining with extended Kalman ﬁlter,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Vehicle state estimation based on min- imum model error criterion combining with extended Kalman ﬁlter,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.697876Z

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Observation ef959508-6103-48b2-b75e-5298bf58168f · outbound

This paper cites Object tracking based on an extended Kalman ﬁlter in high dynamic driving situations,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Object tracking based on an extended Kalman ﬁlter in high dynamic driving situations,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.688164Z

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Observation a1637348-e160-490a-9bb3-e053796faaf4 · outbound

This paper cites A model predictive control approach combined unscented Kalman ﬁlter vehicle state estima- tion in intelligent vehicle trajectory tracking,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving A model predictive control approach combined unscented Kalman ﬁlter vehicle state estima- tion in intelligent vehicle trajectory tracking,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.677457Z

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Observation 51454d73-0a41-43bd-aeb0-9886bf5b2dad · outbound

This paper cites A tutorial on particle ﬁlters for online nonlinear/non-Gaussian Bayesian tracking,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving A tutorial on particle ﬁlters for online nonlinear/non-Gaussian Bayesian tracking,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.666848Z

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Observation 2290dac3-6d40-4d07-bd10-76b717628de7 · outbound

This paper cites Particle ﬁlte r theory and practice with positioning applications,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Particle ﬁlte r theory and practice with positioning applications,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.656654Z

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Observation dec80bd5-0b1f-4b44-a2e9-39fab6c0d625 · outbound

This paper cites A particle-ﬁltering approach for vehicular tracking adaptive to occlu- sions,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving A particle-ﬁltering approach for vehicular tracking adaptive to occlu- sions,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.646574Z

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Observation 45899c26-73ec-4dc7-828e-ae918f25e05a · outbound

This paper cites Evidential grid-based tracking and mapping,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Evidential grid-based tracking and mapping,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.636113Z

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Observation f290e691-6dff-4a2e-bd4d-f63278c71026 · outbound

This paper cites A Bayesian ﬁlter for modeling trafﬁc at stop intersections,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving A Bayesian ﬁlter for modeling trafﬁc at stop intersections,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.626538Z

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Observation 2be30108-ffcc-41a2-8ec4-bc31ceb2f4ce · outbound

This paper cites Interactive scene prediction for automotive applications,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Interactive scene prediction for automotive applications,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.616419Z

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Observation 68a61e72-90d7-442a-a0c8-50db3c234604 · outbound

This paper cites A survey on motion prediction and risk assessment for intelligent vehicles,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving A survey on motion prediction and risk assessment for intelligent vehicles,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.606641Z

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Observation 3904d362-0445-4217-b907-98669d117de1 · outbound

This paper cites Model-based probabilistic collision detection in autonomous driving,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Model-based probabilistic collision detection in autonomous driving,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.596797Z

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Observation 934ee646-87c3-42e7-96ba-10b9bc0a68dc · outbound

This paper cites Generic probabilis- tic interactive situation recognition and prediction: From virtual to real,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Generic probabilis- tic interactive situation recognition and prediction: From virtual to real,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.585690Z

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Observation 2d1cccd1-a90b-418f-a870-00f1e6a5e048 · outbound

This paper cites Safe and feasible motion generation for autonomous driving via constrained policy net,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Safe and feasible motion generation for autonomous driving via constrained policy net,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.575966Z

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Observation 0ee68fc3-c62f-410f-a585-00de004e939f · outbound

This paper cites Dynamic occupancy grid prediction for urban autonomous driving: A deep learning approach with fully automatic labeling,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Dynamic occupancy grid prediction for urban autonomous driving: A deep learning approach with fully automatic labeling,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.566488Z

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Observation 32f97baa-921c-4134-bc98-d7c9aba6bc16 · outbound

This paper cites Kalman ﬁltering with state constraints: A survey of linear and nonlinear algorithms,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Kalman ﬁltering with state constraints: A survey of linear and nonlinear algorithms,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.555823Z

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Observation a2d70c13-d354-42db-b07e-18fa06473f99 · outbound

This paper cites Truncation nonlinear ﬁlters for state estimation with nonlinear inequality constraints,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Truncation nonlinear ﬁlters for state estimation with nonlinear inequality constraints,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.546220Z

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Observation 415d536b-aa84-4801-af62-72f4ac2c1f6b · outbound

This paper cites Bayesian estimation via sequential Monte Carlo sampling— Constrained dynamic systems,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Bayesian estimation via sequential Monte Carlo sampling— Constrained dynamic systems,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.536498Z

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Observation e2811842-d64c-4f48-9c72-686b23ac516c · outbound

This paper cites Constrained Bayesian state estimation—A comparative study and a new particle ﬁlter based approach,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Constrained Bayesian state estimation—A comparative study and a new particle ﬁlter based approach,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.527362Z

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Observation 1288fb52-6771-4778-bb23-a7e450ac756f · outbound

This paper cites Maintaining multimodality through mixture tracking,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Maintaining multimodality through mixture tracking,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.518039Z

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Observation 985937a7-c139-45a2-bf7f-7ea696fbe285 · outbound

This paper cites Probabilistic analysis of dynamic scenes and collision risks assessment to improve driving safety,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Probabilistic analysis of dynamic scenes and collision risks assessment to improve driving safety,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.508839Z

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Observation bdedc8fc-7045-4f4a-9789-2301d6fe2980 · outbound

This paper cites Learni ng and inferring a driver’s braking action in car-following scenarios,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Learni ng and inferring a driver’s braking action in car-following scenarios,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.499184Z

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Observation 22d19544-14ff-442c-a3de-67cbff45ece4 · outbound

This paper cites A layered HMM for predicting motion of a leader in multi-robot settings,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving A layered HMM for predicting motion of a leader in multi-robot settings,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.489266Z

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Observation 5f6c03e1-e354-47d8-b803-bc6ccbfe7163 · outbound

This paper cites Generic vehicle tracking framework capable of handling occlusions based on modiﬁed mixture particle ﬁlter,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Generic vehicle tracking framework capable of handling occlusions based on modiﬁed mixture particle ﬁlter,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.479844Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 35d699ed-4ea8-40b1-9838-ad820bf34751 · outbound

This paper cites Towards a fatality- aware benchmark of probabilistic reaction prediction in highly inter- active driving scenarios,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Towards a fatality- aware benchmark of probabilistic reaction prediction in highly inter- active driving scenarios,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.470071Z

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Observation 1c1ea07b-e59e-4139-ae57-50ccef9b9e29 · outbound

This paper cites Object-oriented Bayesian networks for detection of lane change maneuvers,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Object-oriented Bayesian networks for detection of lane change maneuvers,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.459749Z

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Observation 48bde013-169c-49a0-b71b-7144a34cc3ef · outbound

This paper cites Mobile agent trajectory prediction using Bayesian nonpa rametric reachability trees,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Mobile agent trajectory prediction using Bayesian nonpa rametric reachability trees,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.450118Z

Source-reported events for the cited work

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Observation 6d4732bf-f7f4-4837-b29b-22cb16daa199 · outbound

This paper cites DESIRE: Distant future prediction in dynamic scenes with interacting agents,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving DESIRE: Distant future prediction in dynamic scenes with interacting agents,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.441453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c03cf0e8-c43d-4a0a-9f18-b8dd4e35527b · outbound

This paper cites Wasserstein genera- tive learning with kinematic constraints for probabilistic interactive driving behavior prediction,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Wasserstein genera- tive learning with kinematic constraints for probabilistic interactive driving behavior prediction,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.431362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 54ade5ef-2793-4248-8c6a-f6dc17948ea6 · outbound

This paper cites Interaction-aware multi-agent tracking and probabilistic behavior prediction via adversarial learning,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Interaction-aware multi-agent tracking and probabilistic behavior prediction via adversarial learning,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.421460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dee20b9f-74ef-4034-9435-2b69a142c561 · outbound

This paper cites Conditional generative neural system for probabilistic trajectory prediction,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Conditional generative neural system for probabilistic trajectory prediction,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.410609Z

Source-reported events for the cited work

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Observation b77f9000-e487-4d70-b16a-c93e5f2e84a0 · outbound

This paper cites Coordination and trajectory prediction for vehicle interactions via Bayesian generative modeling,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Coordination and trajectory prediction for vehicle interactions via Bayesian generative modeling,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.400147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 81be10d4-6071-43e4-a810-afb6ddb0f152 · outbound

This paper cites Probabilistic long-term vehicle motion prediction and tracking in large environments,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Probabilistic long-term vehicle motion prediction and tracking in large environments,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.390144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 419a257a-673d-4681-b1d5-61e3da71f101 · outbound

This paper cites Convergence of sequential Monte Carlo meth- ods,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Convergence of sequential Monte Carlo meth- ods,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.380032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation adf8b328-a650-41dd-8c57-8eb16493edd1 · outbound

This paper cites Recursive Monte Carlo ﬁlters: Algorithms and the- oretical analysis,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Recursive Monte Carlo ﬁlters: Algorithms and the- oretical analysis,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.370114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a03d8042-d8f9-4f0d-ad9b-48ca031bfc5d · outbound

This paper cites Comparis on of resampling schemes for particle ﬁltering,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Comparis on of resampling schemes for particle ﬁltering,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.360403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2a49afe2-834c-4060-85ce-b5a30ca58976 · outbound

This paper cites Hidden Markov models and the Baum–Welch algo- rithm,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Hidden Markov models and the Baum–Welch algo- rithm,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.350601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8448723d-c4ec-4f47-9491-62b8a225f9f4 · outbound

This paper cites Recognition, tracking, and optimisation,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Recognition, tracking, and optimisation,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.340603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 594d975d-1f3d-46d6-8b20-6dd35154736e · outbound

This paper cites Modelling the human lane-change execution behaviour through mul- tilayer perceptrons and convolutional neural networks,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Modelling the human lane-change execution behaviour through mul- tilayer perceptrons and convolutional neural networks,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.329493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ed64a1fe-518b-4286-a1ef-e963416f3f88 · outbound

This paper cites Long short-term memory,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Long short-term memory,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.318412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2a036d79-f9d6-40af-834d-a2bced498daa · outbound

This paper cites Progressive Bayes: A new framework for nonlinear state estimation,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Progressive Bayes: A new framework for nonlinear state estimation,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.308210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 56b76a45-0eac-4692-8e08-6ba7d21dabcd · outbound

This paper cites US highway 101 dataset,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving US highway 101 dataset,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.297130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b3fddb67-af40-4573-8e86-f54f591c50a3 · outbound

This paper cites A critical evaluation of the next generation sim- ulation (NGSIM) vehicle trajectory dataset,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving A critical evaluation of the next generation sim- ulation (NGSIM) vehicle trajectory dataset,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.286416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9169acb2-4210-4996-8b2d-8791fa3dd8fc · outbound

This paper cites Comparison and evaluation of advanced motion models for vehicle tracking,.

Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving Comparison and evaluation of advanced motion models for vehicle tracking,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:29:56.274937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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