BBAuthors: Jeong, S.; Advisor: -; Participants: Hester, J. G. D.; Su, W.; Tentzeris, M. M. (2019)
This letter describes the implementation of a machine learning (ML) classification strategy for read/interrogation
enhancement in chipless radio frequency identification (RFID) applications. A novel ML-based approach for classification and of detection tag identifications (IDs) has been presented, which can perform effective transponder readings for a wide variety of ranges and contexts, while providing tag-ID detection accuracy of up to
99.3%. Four tags encoding the four 2 bit IDs were inkjet-printed onto flexible low-cost polyethylene terephtalate substrates and interrogated without crosstalk or clutter interference de-embedding at ranges up to 50 cm, with different orientations and wi... 
