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RF-ray: Joint RF and Linguistics Domain Learning for Object Recognition

on YouTube 06m
Talkat UbiComp 2021 · 2021-09-21..09-26· [machine-learning]

speakers

name:Han Ding
links:none on file
name:Linwei Zhai
links:none on file
name:Cui Zhao
links:none on file
name:Songjiang Hou
links:none on file
name:Ge Wang
links:none on file
name:Wei Xi
links:none on file
name:Jizhong Zhao
links:none on file
name:Yihong Gong
links:none on file

resources

video:https://youtu.be/jm_Egy1GAZ4
slides:none on file

summary

System uses an Impinj reader, one antenna and 7×7 tag array of 49 UHF passive tags, collecting RSS and phase across 7 frequencies and 6 power settings; a sensing‑enhancement module, channel attention, multi‑scale perceptron, environment discriminator, U‑Net for shape and CNN+FC for material produce joint shape and material outputs. Prototype achieves >99% overall, unseen shape‑material pairs >92% accuracy and >97% mIOU for shape, and 92.9% accuracy for zero‑shot linguistic embedding based unseen material prediction.

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