Results 31 to 40 of about 2,299 (249)

Specific Emitter Identification of Frequency Hopping Signals Based on Feature Extraction and Deep Residual Network

IEEE Access, 2022
In the modern war with complex and changeable electromagnetic environment, Specific Emitter Identification (SEI) is an important and difficult problem, which is of great significance in obtaining intelligence information, identifying ourselves or foe ...
Mingdi Li, Jun Xie, Hongjie Yang, Mengjie Geng, Jichuan Liu   +4 more
doaj   +1 more source

Radio Frequency Fingerprint Acquisition and Identification for Small Sample DMR Signals Under Blind Synchronization

IEEE Access
Radio frequency Fingerprint (RFF) is an emerging security technology that identifies devices by utilizing the RF impairments of hardware devices, with the acquisition of fingerprint signals serving as the foundation of fingerprint identification.
Wenlong Gou, Bing Han, Pengfei Sun, Yang Yu, Gang Wu   +4 more
doaj   +1 more source

A RF Fingerprint Based EIoT Device Identification Method

Zhongguo dianli, 2021
Due to the openness nature of the communication medium, the wireless communication of Electric Internet of Things (EIoT) devices faces severe security risks.
Ming LIU, Nian LIU, Xiaoyi HAN, Linning PENG, Hua FU, Yicong CHEN   +5 more
doaj   +1 more source

Label-Efficient Learning for Radio Frequency Fingerprint Identification

2025 IEEE Wireless Communications and Networking Conference (WCNC)
Abstract: Radio Frequency Fingerprint Identification (RF FID) is a novel approach that aims to differentiate devices based on their unique signal transmissions, rather than their given identities. This approach has promising applications in wireless security, spectrum management, and sensing. Current RFFID research uses deep learning due to its success
Nhem, Thayheng, Denoodt, Fabian, Weyn, Maarten, Peeters, Michael, Oramas, José, Berkvens, Rafael   +5 more
openaire   +2 more sources

Receiver-Agnostic Radio Frequency Fingerprint Identification via Federated Learning

IEEE Transactions on Machine Learning in Communications and Networking
Ensuring secure and reliable wireless connectivity is essential for modern Internet of Things (IoT) applications. Radio frequency fingerprint identification (RFFI) has emerged as a promising lightweight device authentication mechanism by leveraging ...
Faiza Gul, Xiangyun Zhou, Amanda S. Barnard, Salman Durrani   +3 more
doaj   +1 more source

A Deep Learning-Based Human Identification System With Wi-Fi CSI Data Augmentation

IEEE Access, 2021
Human identification systems generally include face recognition, iris recognition, radio frequency identification tags, and fingerprint recognition systems.
Hyunggeun Mo, Seungku Kim
doaj   +1 more source

Raman‐based label‐free microscopic analysis of the pancreas in living zebrafish larvae

FEBS Open Bio, EarlyView.
Forward stimulated Raman scattering (F‐SRS) and epi coherent anti‐Stokes Raman scattering (E‐CARS) allow label‐free discrimination of distinct subcellular structures in the pancreas of living zebrafish larvae. Given the straightforward applicability, we anticipate broad implementation of Raman microscopy in other organs and across various biomedical ...
Noura Faraj, Eline M. F. de Lange, Klaas A. Sjollema, Ben N. G. Giepmans   +3 more
wiley   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Toward Length-Versatile and Noise-Robust Radio Frequency Fingerprint Identification

IEEE Transactions on Information Forensics and Security, 2023
Radio frequency fingerprint identification (RFFI) can classify wireless devices by analyzing the signal distortions caused by the intrinsic hardware impairments. State-of-the-art neural networks have been adopted for RFFI. However, many neural networks, e.g., multilayer perceptron (MLP) and convolutional neural network (CNN), require fixed-size input ...
Guanxiong Shen, Junqing Zhang, Alan Marshall 0001, Mikko Valkama, Joseph R. Cavallaro   +4 more
openaire   +4 more sources

Receptor‐Free Identification of Toxic Gases Enabled by Hygroscopic Aqueous Salt Films

Advanced Functional Materials, EarlyView.
Water as a gas sensor coating sounds impossible—until it stops evaporating. Here, hygroscopic salt solutions (LiCl, LiBr, H3PO4) form non‐drying aqueous films on CNT chemiresistors under ambient air. Gases partition into these liquid layers, sometimes transforming into water, and generate salt‐specific resistance fingerprints across a four‐channel ...
Seongwoo Lee, Yun‐Tae Kim, Hwarang Choi, Sanghwan Park, Seongyeop Lim, Chang Young Lee   +5 more
wiley   +1 more source