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RF-ray puts the object approximate to an RFID tag array, and explores the propagation effect as well as coupling effect between RFIDs and the object for sensing. In contrast to prior proposals, RF-ray is capable to recognize unseen objects, including unseen shape-material pairs and unseen materials within a certain container. To make it real, RF-ray introduces a sensing capability enhancement module and leverages a two-branch neural network for shape profiling and material identification respectively. Furthermore, we incorporate a Zero-Shot Learning based embedding module that incorporates the well-learned linguistic features to generalize RF-ray to recognize unseen materials. We build a prototype of RF-ray using commodity RFID devices. Comprehensive real-world experiments demonstrate our system can achieve high object recognition performance.<\/jats:p>","DOI":"10.1145\/3478115","type":"journal-article","created":{"date-parts":[[2021,9,14]],"date-time":"2021-09-14T22:48:23Z","timestamp":1631659703000},"page":"1-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["RF-ray"],"prefix":"10.1145","volume":"5","author":[{"given":"Han","family":"Ding","sequence":"first","affiliation":[{"name":"Xi'an Jiaotong University, School of Computer Science and Technology, Xi'an, China"}]},{"given":"Linwei","family":"Zhai","sequence":"additional","affiliation":[{"name":"Xi'an Jiaotong University, School of Software and Engineering, Xi'an, China"}]},{"given":"Cui","family":"Zhao","sequence":"additional","affiliation":[{"name":"Xi'an Jiaotong University, School of Cyber Science and Engineering, Xi'an, China"}]},{"given":"Songjiang","family":"Hou","sequence":"additional","affiliation":[{"name":"Xi'an Jiaotong University, School of Computer Science and Technology, Xi'an, China"}]},{"given":"Ge","family":"Wang","sequence":"additional","affiliation":[{"name":"Xi'an Jiaotong University, School of Computer Science and Technology, Xi'an, China"}]},{"given":"Wei","family":"Xi","sequence":"additional","affiliation":[{"name":"Xi'an Jiaotong University, School of Computer Science and Technology, Xi'an, China"}]},{"given":"Jizhong","family":"Zhao","sequence":"additional","affiliation":[{"name":"Xi'an Jiaotong University, School of Computer Science and Technology, Xi'an, China"}]},{"given":"Yihong","family":"Gong","sequence":"additional","affiliation":[{"name":"Xi'an Jiaotong University, School of Software and Engineering, Xi'an, China"}]}],"member":"320","published-online":{"date-parts":[[2021,9,14]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"https:\/\/www.hstoday.us\/industry\/dhs-awards-200k-for-ai-based-proof-of-concept-for-tsa\/. 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