239   Artículos

 
en línea
Zhenyu Yin, Feiqing Zhang, Guangyuan Xu, Guangjie Han and Yuanguo Bi    
Confronting the challenge of identifying unknown fault types in rolling bearing fault diagnosis, this study introduces a multi-scale bearing fault diagnosis method based on transfer learning. Initially, a multi-scale feature extraction network, MBDCNet, ... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Yupu Huang, Li Zhuo and Jingjing Cao    
Accurately measuring industrial spatial agglomeration patterns is crucial for promoting regional economic development. However, few studies have considered both agglomeration degrees and cluster locations of industries. Moreover, the traditional multi-sc... ver más
Revista: ISPRS International Journal of Geo-Information    Formato: Electrónico

 
en línea
Xiaobing Xu and Yaping Zhang    
Running posture estimation is a specialized task in human pose estimation that has received relatively little research attention due to the lack of appropriate datasets. To address this issue, this paper presents the construction of a new benchmark datas... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Linhua Zhang, Ning Xiong, Wuyang Gao and Peng Wu    
With the exponential growth of remote sensing images in recent years, there has been a significant increase in demand for micro-target detection. Recently, effective detection methods for small targets have emerged; however, for micro-targets (even fewer... ver más
Revista: Information    Formato: Electrónico

 
en línea
Yuting Chen, Pengjun Zhao, Yi Lin, Yushi Sun, Rui Chen, Ling Yu and Yu Liu    
Precise identification of spatial unit functional features in the city is a pre-condition for urban planning and policy-making. However, inferring unknown attributes of urban spatial units from data mining of spatial interaction remains a challenge in ge... ver más
Revista: ISPRS International Journal of Geo-Information    Formato: Electrónico

 
en línea
Chuanyun Xu, Hang Wang, Yang Zhang, Zheng Zhou and Gang Li    
Few-shot learning refers to training a model with a few labeled data to effectively recognize unseen categories. Recently, numerous approaches have been suggested to improve the extraction of abundant feature information at hierarchical layers or multipl... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Changhong Liu, Jiawen Wen, Jinshan Huang, Weiren Lin, Bochun Wu, Ning Xie and Tao Zou    
Underwater object detection is crucial in marine exploration, presenting a challenging problem in computer vision due to factors like light attenuation, scattering, and background interference. Existing underwater object detection models face challenges ... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Pengfei Ning, Dianjun Zhang, Xuefeng Zhang, Jianhui Zhang, Yulong Liu, Xiaoyi Jiang and Yansheng Zhang    
The Array for Real-time Geostrophic Oceanography (Argo) program provides valuable data for maritime research and rescue operations. This paper is based on Argo historical and satellite observations, and inverted sea surface and submarine drift trajectori... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Chenhong Yan, Shefeng Yan, Tianyi Yao, Yang Yu, Guang Pan, Lu Liu, Mou Wang and Jisheng Bai    
Ship-radiated noise classification is critical in ocean acoustics. Recently, the feature extraction method combined with time?frequency spectrograms and convolutional neural networks (CNNs) has effectively described the differences between various underw... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Zhendong He, Wenbin Yang, Yanjie Liu, Anping Zheng, Jie Liu, Taishan Lou and Jie Zhang    
Ensuring the safety of transmission lines necessitates effective insulator defect detection. Traditional methods often need more efficiency and accuracy, particularly for tiny defects. This paper proposes an innovative insulator defect recognition method... ver más
Revista: Information    Formato: Electrónico

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