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cs.LG2024
MMBind: Unleashing the Potential of Distributed and Heterogeneous Data for Multimodal Learning in IoT
Xiaomin Ouyang, Jason Wu, Tomoyoshi Kimura +4
Multimodal sensing systems are increasingly prevalent in various real-world applications. Most existing multimodal learning approaches heavily rely on training with a large amount…
cs.CV2024
FlexLoc: Conditional Neural Networks for Zero-Shot Sensor Perspective Invariance in Object Localization with Distributed Multimodal Sensors
Jason Wu, Ziqi Wang, Xiaomin Ouyang +5
Localization is a critical technology for various applications ranging from navigation and surveillance to assisted living. Localization systems typically fuse information from sen…
cs.RO2024
GDTM: An Indoor Geospatial Tracking Dataset with Distributed Multimodal Sensors
Ho Lyun Jeong, Ziqi Wang, Colin Samplawski +6
Constantly locating moving objects, i.e., geospatial tracking, is essential for autonomous building infrastructure. Accurate and robust geospatial tracking often leverages multimod…