Dec 12, 2023 · In this article, we propose a novel identification method that combines the deep neural network (DNN) and the unsupervised clustering.

Jul 16, 2024 · In this design, after offline training, the triplet loss convolutional neural network (TLCNN) can be utilized to extract the features of the ...

Apr 9, 2024 · Abstract—By exploiting the inherent hardware characteristics of wireless devices, radio frequency fingerprint identification.

Article on Triplet Network and Unsupervised-Clustering-Based Zero-Shot Radio Frequency Fingerprint Identification With Extremely Small Sample Size, ...

Triplet Network and Unsupervised Clustering Based Zero-Shot Radio Frequency Fingerprint Identification With Extremely Small Sample Size. Haotian Zhang 1.

In this design, after offline training, the triplet loss convolutional neural network (TLCNN) can be utilized to extract the features of the radio frequency ...

Triplet Network and Unsupervised-Clustering-Based Zero-Shot Radio Frequency Fingerprint Identification With Extremely Small Sample Size. Haotian Zhang, Lei ...

Triplet Network and Unsupervised-Clustering-Based Zero-Shot Radio Frequency Fingerprint Identification With Extremely Small Sample Size. Triplet Network and ...

Triplet Network and Unsupervised-Clustering-Based Zero-Shot Radio Frequency Fingerprint Identification With Extremely Small Sample Size.

3 Excerpts. Triplet Network and Unsupervised-Clustering-Based Zero-Shot Radio Frequency Fingerprint Identification With Extremely Small Sample Size.