Results 51 to 60 of about 3,557 (290)

Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles

Advanced Materials, EarlyView.
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung, Jiaxiang Yi, Hieu Nguyen‐Duc, Tien Nu Hoang Lo, Weili Zhao, Chaoqun Dong, Fabien Sorin, Baris Caglar, Lei Wei, Tung Nguyen‐Dang   +9 more
wiley   +1 more source

Automatic target recognition by means of polarimetric ISAR images: a model matching based algorithm

, 2008
Automatic target recognition (ATR) is generally the reason why ISAR imaging systems are employed. Moreover, the use of fully polarimetric radar systems in radar imaging applications such as SAR and ISAR has enhanced both image quality and classification ...
L. Demi, Berizzi, F., F. Berizzi, GIUSTI E, BATES B., Giusti, E., Bates, B., Cacciamano, A., DEMI L, Demi, L., CACCIAMANO A, B. Bates, ZHOU A, E. Giusti, MARTORELLA, MARCO, M. Martorella, Martorella, M., Zhou, Z., BERIZZI, FABRIZIO, Z. Zhou, A. Cacciamano   +20 more
core   +1 more source

Ti3C2Tx MXene/Silver Composite Foams For Lightweight, High‐Performance Electromagnetic Interference Shielding and Joule Heating

Advanced Materials Interfaces, EarlyView.
Ultrathin MXene/EMF composite foams achieve a specific shielding efficiency of 749.6 dB.dB·cm3$\mathrm{dB}\cdot {\mathrm{cm}}^{3}$/g, while the silver‐enhanced MXene/Ag/EMF reaches 81.4 dB shielding effectiveness at just 1.0 mm thickness. Both composites exhibit rapid Joule heating, retain stability up to 250∘C$^\circ{\rm C}$, and withstand 1000 ...
Abdullah A. Mahmood, Mingxuan Li, Vahid Rad, Mehdi Zarei, Chen‐Yu Yeh, Masoud Soroush, Guangyong Li, Paul W. Leu   +7 more
wiley   +1 more source

Multi-Aspect SAR Target Recognition Based on Non-Local and Contrastive Learning

Mathematics, 2023
Synthetic aperture radar (SAR) automatic target recognition (ATR) has been widely applied in multiple fields. However, the special imaging mechanism of SAR results in different visual features of the same target at different azimuth angles, so single ...
Xiao Zhou, Siyuan Li, Zongxu Pan, Guangyao Zhou, Yuxin Hu   +4 more
doaj   +1 more source

A 2D processing algorithm for detecting landmines using Ground Penetrating Radar data [PDF]

, 2012
Ground Penetrating Radar(GPR) is one of a number of technologies that have been used to improve landmine detection efficiency. The clutter environment within the first few cm of the soil where landmines are buried, exhibits strong reflections with ...
Cockshott, W.P., Sengodan, A.
core  

End‐to‐End Sensing Systems for Breast Cancer: From Wearables for Early Detection to Lab‐Based Diagnosis Chips

Advanced Materials Technologies, EarlyView.
This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane, Lyn I. Jones, Richard M. Martin, Helen Winter, Faezeh Arab Hassani   +4 more
wiley   +1 more source

Introduction to Drone Detection Radar with Emphasis on Automatic Target Recognition (ATR) technology

CoRR, 2023
This paper discusses the challenges of detecting and categorizing small drones with radar automatic target recognition (ATR) technology. The authors suggest integrating ATR capabilities into drone detection radar systems to improve performance and manage emerging threats. The study focuses primarily on drones in Group 1 and 2.
Jiangkun Gong, Jun Yan 0006, Deyong Kong, Deren Li   +3 more
openaire   +2 more sources

Multiple feature-enhanced SAR imaging using sparsity in combined dictionaries [PDF]

, 2013
Nonquadratic regularization-based image formation is a recently proposed framework for feature-enhanced radar imaging. Specific image formation techniques in this framework have so far focused on enhancing one type of feature, such as strong point ...
Çetin, Müjdat, Samadi, Sadegh, Masnadi-Shirazi, Mohammad Ali   +2 more
core   +1 more source

Transducers Across Scales and Frequencies: A System‐Level Framework for Multiphysics Integration and Co‐Design

Advanced Materials Technologies, EarlyView.
Transducers convert physical signals into electrical and optical representations, yet each mechanism is bounded by intrinsic trade‐offs across bandwidth, sensitivity, speed, and energy. This review maps transduction mechanisms across physical scale and frequency, showing how heterogeneous integration and multiphysics co‐design transform isolated ...
Aolei Xu, Mengyao Xiao, Zhouli Sui, Yinpeng Wang, Daoye Zheng, Yuxin Liu, Luwei Wang, Huajun Liu, Chengkuo Lee   +8 more
wiley   +1 more source

Deep-Learning for Radar: A Survey

IEEE Access, 2021
A comprehensive and well-structured review on the application of deep learning (DL) based algorithms, such as convolutional neural networks (CNN) and long-short term memory (LSTM), in radar signal processing is given.
Zhe Geng, He Yan, Jindong Zhang, Daiyin Zhu   +3 more
doaj   +1 more source