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Found 3 papers, 1 papers with code
IMU2CLIP: Multimodal Contrastive Learning for IMU Motion Sensors from Egocentric Videos and Text
We present IMU2CLIP, a novel pre-training approach to align Inertial Measurement Unit (IMU) motion sensor recordings with video and text, by projecting them into the joint representation space of Contrastive Language-Image Pre-training (CLIP).
Geometric Learning and Topological Inference with Biobotic Networks: Convergence Analysis
Local interactions are used to create a graphical representation referred to as the encounter graph.
Robust Topological Feature Extraction for Mapping of Environments using Bio-Inspired Sensor Networks
A probabilistic motion model of mobile sensing nodes, inspired by motion characteristics of cockroaches, is utilized to extract weak encounter information in order to build a topological representation of the environment.
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