Results 111 to 120 of about 48,420 (287)

A Residual Optronic Convolutional Neural Network for SAR Target Recognition

Photonics
Deep learning (DL) has shown great capability in remote sensing and automatic target recognition (ATR). However, huge computational costs and power consumption are challenging the development of current DL methods.
Ziyu Gu, Zicheng Huang, Xiaotian Lu, Hongjie Zhang, Hui Kuang   +4 more
doaj   +1 more source

Ship target recognition based on superstructure matching [PDF]

E3S Web of Conferences
The Automatic Target Recognition(ATR) of ship targets based on Inverse Synthetic Aperture Radar(ISAR) images plays a significant role in naval warfare.To address the issue that existing superstructure-based recognition methods do not fully use ...
Deng Jie, Su Fulin
doaj   +1 more source

Automatic target recognition using passive bistatic radar signals.

Reconnaissance automatique de cibles par utilisation de signaux de radars passifs bistatiques Dans cette thèse, nous présentons la conception, le développement et le test de trois systèmes de reconnaissance automatique de cibles (ATR) visant à reconnaître des avions non-coopératifs, c’est-à-dire des avions ne fournissant par leur ...
openaire   +2 more sources

Smart Flexible Tactile Sensors: Recent Progress in Device Designs, Intelligent Algorithms, and Multidisciplinary Applications

Advanced Intelligent Discovery, EarlyView.
Flexible tactile sensors have considerable potential for broad application in healthcare monitoring, human–machine interfaces, and bioinspired robotics. This review explores recent progress in device design, performance optimization, and intelligent applications. It highlights how AI algorithms enhance environmental adaptability and perception accuracy
Siyuan Wang, Ming Dong, Rongrong Bao, Caofeng Pan   +3 more
wiley   +1 more source

Analysis of Radar Doppler Signature from Human Data [PDF]

, 2014
This paper presents the results of time (autocorrelation) and time-frequency (spectrogram) analyses of radar signals returned from the moving human targets.
Andrić, M., Bondzulić, B., Bujaković, D., Simić, S., Zrnić, B.   +4 more
core   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

SAR ATR with full-angle data augmentation and feature polymerisation

The Journal of Engineering, 2019
Utilising neural networks to learn and extract valuable features has achieved satisfactory performance for synthetic aperture radar automatic target recognition (SAR ATR).
Yikui Zhai, Hui Ma, Jian Liu, Wenbo Deng, Lijuan Shang, Bing Sun, Ziyi Jiang, Huixin Guan, Yihang Zhi, Xi Wu, Jihua Zhou   +10 more
doaj   +1 more source

AS‐pHopt: An Optimal pH Prediction Model Enhanced by Active Site of Enzymes

Advanced Intelligent Discovery, EarlyView.
To address the low accuracy of enzyme optimal pH (pHopt) prediction, this study develops active site‐based pHopt (AS‐pHopt), a prediction model enhanced by active site information and pseudo‐label prediction. Integrating key structural and physicochemical features affecting enzyme pHopt, AS‐pHopt uses Evolutionary Scale Modeling (ESM)‐2 with active ...
Wenxiang Song, Xinmin Li, Hongbo Yu, Le Xiong, Guixia Liu, Weihua Li, Yun Tang   +6 more
wiley   +1 more source

Lidar‐Based Object Tracking of Traffic Participants with Sensor Nodes in Existing Urban Infrastructure

Advanced Intelligent Systems, EarlyView.
This paper presents a lidar‐based sensor node design and a rule‐based state observer for edge‐based traffic participant tracking. Unlike other state‐of‐the‐art methods, this state observer enables real‐time, CPU‐only edge processing without relying on machine learning approaches.
Simon Schäfer, Bassam Alrifaee, Ehsan Hashemi   +2 more
wiley   +1 more source

Concentric Rheostat Decoupled 3D Force‐Sensing Module for Smart Table Tennis Training

Advanced Intelligent Systems, EarlyView.
A 3D‐printed sensor array intrinsically decouples normal and shear forces through a unique concentric structural design. By integrating piezoresistive, sliding area‐varying capacitive, and concentric rheostat mechanisms, the 12‐sensor module achieves high‐resolution 3D force mapping without complex algorithms.
Zhe Liu, Kunlin Wu, Bingrui Sim, Wenjie Lai, Xingyu Chen, Jiajun Liu, Yifan Wang, Soo Jay Phee   +7 more
wiley   +1 more source