Data

Chipless RFID 2D Train and Validation Dataset

Monash University
Larry M. Arjomandi (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.26180/20444058.v2&rft.title=Chipless RFID 2D Train and Validation Dataset&rft.identifier=https://doi.org/10.26180/20444058.v2&rft.publisher=Monash University&rft.description=For 27 tags, 1D frequency scanning is done and it's virtually converted to 2D as per Section V of the article L. M. Arjomandi, G. Khadka and N. C. Karmakar, mm-Wave Chipless RFID Decoding: Introducing Image-Based Deep Learning Techniques, in IEEE Transactions on Antennas and Propagation, vol. 70, no. 5, pp. 3700-3709, May 2022, doi: 10.1109/TAP.2021.3137197&rft.creator=Larry M. Arjomandi&rft.date=2022&rft_rights=CC-BY-SA-4.0&rft_subject=mm-wave imaging&rft_subject=Chipless tags&rft_subject=2D virtual images of 1D freq data&rft.type=dataset&rft.language=English Access the data

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CC-BY-SA-4.0

Full description

For 27 tags, 1D frequency scanning is done and it's virtually converted to 2D as per Section V of the article

L. M. Arjomandi, G. Khadka and N. C. Karmakar, "mm-Wave Chipless RFID Decoding: Introducing Image-Based Deep Learning Techniques," in IEEE Transactions on Antennas and Propagation, vol. 70, no. 5, pp. 3700-3709, May 2022, doi: 10.1109/TAP.2021.3137197

Issued: 2022-08-06

Created: 2022-08-06

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Identifiers
ACN 633 798 857