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Target tracking in heterogeneous sensor networks using audio and video sensor fusion.

, , , , and . MFI, page 14-19. IEEE, (2008)

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Target tracking in heterogeneous sensor networks using audio and video sensor fusion., , , , and . MFI, page 14-19. IEEE, (2008)Tracking in Urban Environments Using Sensor Networks Based on Audio-Video Fusion., , , , and . Handbook of Ambient Intelligence and Smart Environments, Springer, (2010)NestedNet: Learning Nested Sparse Structures in Deep Neural Networks, , and . (2017)cite arxiv:1712.03781Comment: To appear in CVPR 2018. Spotlight Presentation.Chance-constrained target tracking using sensors with bounded fan-shaped sensing regions., , and . Auton. Robots, 42 (2): 307-327 (2018)Text2Action: Generative Adversarial Synthesis from Language to Action., , , , and . ICRA, page 1-5. IEEE, (2018)Human behavior prediction for smart homes using deep learning., , and . RO-MAN, page 173-179. IEEE, (2013)Visual tracking of non-rigid objects with partial occlusion through elastic structure of local patches and hierarchical diffusion., , , , , and . Image Vis. Comput., (2015)Interactive Text2Pickup Networks for Natural Language-Based Human-Robot Collaboration., , , , and . IEEE Robotics Autom. Lett., 3 (4): 3308-3315 (2018)Nonconvex Sparse Representation With Slowly Vanishing Gradient Regularizers., , and . IEEE Access, (2020)Local Selective Vision Transformer for Depth Estimation Using a Compound Eye Camera., , , and . Pattern Recognit. Lett., (March 2023)