Results 71 to 80 of about 3,557 (290)

SAR Automatic Target Recognition Using a Roto-Translational Invariant Wavelet-Scattering Convolution Network

Remote Sensing, 2018
The algorithm of synthetic aperture radar (SAR) for automatic target recognition consists of two stages: feature extraction and classification. The quality of extracted features has significant impacts on the final classification performance.
Haipeng Wang, Suo Li, Yu Zhou, Sizhe Chen   +3 more
doaj   +1 more source

Cross‐Scale Hierarchical Targeted Delivery System Based on Small‐Scale Magnetic Robots

Advanced Robotics Research, EarlyView.
This article reviews a cross‐scale hierarchical targeted delivery system that integrates magnetic continuum robots and magnetic microrobots. By combining rapid long‐range navigation with precise microscale targeting, the system overcomes key limitations of single‐scale approaches.
Junjian Zhou, Zhiqiang Chen, Yuanbiao Ma, Zhiqiang Tang, Qianqian Wang   +4 more
wiley   +1 more source

HRRP Unsupervised Target Feature Extraction Method Based on Multiple Contrastive Loss in Radar Sensor Networks

Leida xuebao
In recent years, target recognition systems based on radar sensor networks have been widely studied in the field of automatic target recognition. These systems observe the target from multiple angles to achieve robust recognition, which also brings the ...
Hao WAN, Jing LIANG
doaj   +1 more source

Schooling Trajectories and the Development of Brain Dynamics: A Comparative Study of Montessori and Traditional Education

Advanced Science, EarlyView.
We investigate whether Montessori and traditional schooling systems shape the developmental trajectory of large‐scale brain dynamics in different ways. We quantify the arrow of time (“non‐reversibility”) in neural activity during resting state and movie‐watching, revealing distinct maturational patterns.
Elvira del Agua, Anira Escrichs, Yonatan Sanz Perl, Morten L. Kringelbach, Adele Diamond, Solange Denervaud, Gustavo Deco   +6 more
wiley   +1 more source

Transferable Deep Reinforcement Learning With Edge‐Contour‐Depth Fusion for Autonomous Wireless Capsule Endoscopy Navigation

Advanced Science, EarlyView.
This study presents an anatomical landmark‐guided DRL framework for autonomous wireless capsule endoscopy navigation. Using a lightweight edge‐contour‐depth fusion module, it achieves over 97% coverage across diverse gastric anatomies. To ensure reliability, a two‐stage sim‐to‐real pipeline with an adaptive dynamic programming controller mitigates ...
Haoxuan Wu, Haitao Gao, Qingyang Liu, Sishen Yuan, Haiyang Fang, Mingwu Su, Baijia Liang, Yongzun Yang, Long Bai, Wenzhen Dong, Dihong Xie, Shijian Su, Jiewen Lai, Shing Shin Cheng, Zhen Li, Xiuli Zuo, Hongliang Ren   +16 more
wiley   +1 more source

WTAP‐Mediated m6A Modification Targets the LRP1‐Lipid Metabolism Axis to Regulate Joint Cartilage Regeneration

Advanced Science, EarlyView.
WTAP drives cartilage regeneration by activating an LRP1‐dependent lipid metabolic program in macrophages, enhancing IL‐10 and TGF‐β secretion to promote chondrogenic differentiation. Leveraging this mechanism, virtual screening identifies LRP1‐targeting compounds that effectively stimulate cartilage repair, highlighting a druggable epigenetic ...
Chenyan Huang, Chenyu Deng, Zhengrong Gao, Chen Chen, Huimin Zheng, Yue Yang, Yan Wei   +6 more
wiley   +1 more source

THE PERFORMANCE ANALYSIS OF STFT-ANFIS CLASSIFICATION METHOD ON PULSED RADAR TARGET CATEGORIZATION

Electrica
In this paper, a pattern recognition system is developed for automatic classification of the radar target signals. Feature extraction is an important subset of the pattern recognition system.
Engin AVCI, İbrahim TURKOGLU, Mustafa POYRAZ   +2 more
doaj   +2 more sources

Radar HRRP Target Recognition via Semi-Supervised Multi-Task Deep Network

IEEE Access, 2019
Feature representation based on the high resolution range profile (HRRP) is the key technology in radar automatic target recognition(RATR). In this paper, we design a deep-u-blind denoising network(DUBDNet) to extract features with high-noise-stability ...
Chenkai Zhao, Xudong He, Jing Liang, Tiantian Wang, Changba Huang   +4 more
doaj   +1 more source

Combining Spatial Multi‐Omics Data to Decipher Spatial Domains and Elucidate Cell Heterogeneity Based on Self‐Supervised Graph Learning

Advanced Science, EarlyView.
A self‐supervised multi‐view graph fusion framework integrates spatial multi‐omics, excelling in domain identification and denoising. It reconstructs spatial pseudo‐expression, jointly analyzes multi‐omics data, infers RNA velocity, predicts spatial omics features from single‐cell multi‐omics, and detects spatially dark genes and transcription factors,
Yuejing Lu, Rui Qiao, Ying Li, Junhong Li, Nuoya Yue, Jing Ge, Jiao Wang, Luonan Chen, Peiluan Li   +8 more
wiley   +1 more source

PancDS in Real‐World Practice: A Prospective Multicenter Validation of a Clinical Decision‐Support System Bridging Experience Gaps in Pancreatic Lesion Diagnosis

Advanced Science, EarlyView.
A biomimetic artificial intelligence system, PancDS, has been developed to distinguish pancreatic ductal adenocarcinoma from mass‐forming pancreatitis by adaptively integrating clinical data, radiomics, and deep learning features. Validated across multicenter, reader‐study, and prospective settings, PancDS improves diagnostic accuracy, particularly for
Zhibo Wang, Weinuo Qu, Wenwen Cai, Chuhuai Wang, Chenxi Lyu, Qingguo Xie, Qian Chu, Yaqi Shen, Peng Xiao, Feng Li, Qingpeng Zhang, Jiali Li, Jeong Min Lee, Zhen Li   +13 more
wiley   +1 more source