Multi-Modal Cross Learning for an FMCW Radar Assisted by Thermal and RGB Cameras to Monitor Gestures and Cooking Processes

This paper proposes a multi-modal cross learning approach to augment the neural network training phase by additional sensor data. The approach is multi-modal during training (i.e., radar Range-Doppler maps, thermal camera images, and RGB camera images are used for training). In inference, the approa...

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Vydané v:	IEEE access Ročník 9; s. 22295 - 22303
Hlavní autori:	Altmann, Marco, Ott, Peter, Stache, Nicolaj C., Waldschmidt, Christian
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	autoencoder Cameras Classification Coders Cooking cross learning Decoding Gesture recognition Learning Machine learning modality hallucination multimodal sensors Neural networks Occupancy Radar radar applications Radar imaging Radar range range-doppler Sensors Task analysis thermal camera Training User interfaces
ISSN:	2169-3536, 2169-3536
On-line prístup:	Získať plný text
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