Results 101 to 110 of about 1,902,052 (207)

Organometallic Solution and Surface Routes to Highly Dispersed Carbon Nanotube‐Based Fe–N–C Electrocatalysts

Small Structures, Volume 7, Issue 11, November 2026.
Isolated Fe–N–C sites embedded in an extended 3D carbon framework are accessible under ambient conditions without pyrolysis for the first time. 57Fe Mössbauer, XANES, and EPR spectroscopy reveals iron in intermediate Fe>2+ and Fe3+ spin states with long‐range magnetic coupling between iron centers which are catalytically active in ORR.
Jörg J. Schneider, Chandrajeet Mohapatra, Johannes M. Emmert, Isabel M. Teichert, Jörg Engstler, Anna A. Makarova, Kirill V. Yusenko, Maciej Oskar Liedke, Ahmed G. Attallah, Maik Butterling, Andreas Wagner, Di Wang, Christian Kübel, Arpad Rostas, Emre Erdem, Martin Panthöfer, Angela Möller   +16 more
wiley   +1 more source

Through-the-Wall Radar Human Activity Micro-Doppler Signature Representation Method Based on Joint Boulic-Sinusoidal Pendulum Model [PDF]

With the help of micro-Doppler signature, ultra-wideband (UWB) through-the-wall radar (TWR) enables the reconstruction of range and velocity information of limb nodes to accurately identify indoor human activities.
Yang, Xiaopeng, Qu, Xiaodong, Ma, Zeyu, Zhang, Hao, Gao, Weicheng   +4 more
core   +1 more source

Enhancement of Drone ISAR Imaging Through Isolation and Suppression of Micro-Doppler Effects

IEEE Access
Increasing concerns over the use of drones for military or hostile purposes have intensified the demand for effective detection and countermeasures. Although conventional acoustic, thermal, and optical sensors have been extensively explored, active radar
Kyoung-Min Song, Woo-Kyung Lee
doaj   +1 more source

Generation of Human Micro-Doppler Signature Based on Layer-Reduced Deep Convolutional Generative Adversarial Network. [PDF]

Comput Intell Neurosci, 2022
Ostovan M, Samadi S, Kazemi A.
europepmc   +1 more source

Automated classification of micro-doppler signature

, 2017
This report is regarding the Final Year Project A3090-161 on the topic of Automated Classification of Micro-Doppler Signature. It discusses how gait recognition is achieved through the analysis of micro-Doppler features.
Zhao, Dawei
core  

A New Method for Traffic Participant Recognition Using Doppler Radar Signature and Convolutional Neural Networks

Sensors
The latest survey results show an increase in accidents on the roads involving pedestrians and cyclists. The reasons for such situations are many, the fault actually lies on both sides.
Błażej Ślesicki, Anna Ślesicka
doaj   +1 more source

Cross-frequency training with adversarial learning for radar micro-Doppler signature classification

This dataset presents the micro-Doppler spectrogram data used in the paper titled "Cross-frequency training with adversarial learning for radar micro-Doppler signature classification"
Rahman, Mahbubur (Mahbub), Fioranelli, Francesco, Kurtoglu, Emre, Gurbuz, Sevgi Zubeyde, Macks, Trevor   +4 more
core   +1 more source

Human Anomalous Gait Termination Recognition via Through-the-wall Radar Based on Micro-Doppler Corner Features and Non-Local Mechanism

Leida xuebao
Through-the-wall radar can penetrate walls and realize indoor human target detection. Deep learning is commonly used to extract the micro-Doppler signature of a target, which can be used to effectively identify human activities behind obstacles. However,
Xiaopeng YANG, Weicheng GAO, Xiaodong QU
doaj   +1 more source

Micro-doppler processing for ultra-wideband radar data

, 2012
In this paper, we describe an operational pulse Doppler radar imaging system for indoor target localization and classification, and show how a target’s micro-Doppler signature (µDS) can be processed when ultra-wideband (UWB) waveforms are employed ...
Fauzia Ahmad, Moeness G. Amin, Graeme E. Smith   +2 more
core   +1 more source

Three-Dimensional Human Pose Estimation from Micro-Doppler Signature Based on SISO UWB Radar

Remote Sensing
In this paper, we propose an innovative approach for transforming 2D human pose estimation into 3D models using Single Input–Single Output (SISO) Ultra-Wideband (UWB) radar technology.
Xiaolong Zhou, Tian Jin, Yongpeng Dai, Yongping Song, Kemeng Li   +4 more
doaj   +1 more source