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Shun Wang, Jiayan Wang, Zhikang Xu, Ji Wang, Rui Li and Jinliang Dai
The application of titanium alloy in shipbuilding can reduce ship weight and carbon emissions. To solve the problem of titanium alloy forming, the deformation prediction of titanium alloy line heating based on a backpropagation (BP) neural network and sp...
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Feng Zhou, Shijing Hu, Xin Du, Xiaoli Wan and Jie Wu
In the current field of disease risk prediction research, there are many methods of using servers for centralized computing to train and infer prediction models. However, this centralized computing method increases storage space, the load on network band...
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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...
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Min Hao, Quan Sun, Chuanzhong Xuan, Xiwen Zhang, Minghui Zhao and Shuo Song
To achieve automated farming management, including the recording, tracking, and statistics of sheep, we harness deep learning technology for sheep face recognition research, and the further development of lightweight sheep face recognition models. Deep l...
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Yuntao Shi, Qi Luo, Meng Zhou, Wei Guo, Jie Li, Shuqin Li and Yu Ding
Objects thrown from tall buildings in communities are characterized by their small size, inconspicuous features, and high speed. Existing algorithms for detecting such objects face challenges, including excessive parameters, overly complex models that ar...
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Rujia Li, Yadong Li, Weibo Qin, Arzlan Abbas, Shuang Li, Rongbiao Ji, Yehui Wu, Yiting He and Jianping Yang
This research tackles the intricate challenges of detecting densely distributed maize leaf diseases and the constraints inherent in YOLO-based detection algorithms. It introduces the GhostNet_Triplet_YOLOv8s algorithm, enhancing YOLO v8s by integrating t...
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Ying Chen, Xi Qiao, Feng Qin, Hongtao Huang, Bo Liu, Zaiyuan Li, Conghui Liu, Quan Wang, Fanghao Wan, Wanqiang Qian and Yiqi Huang
Invasive plant species pose significant biodiversity and ecosystem threats. Real-time identification of invasive plants is a crucial prerequisite for early and timely prevention. While deep learning has shown promising results in plant recognition, the u...
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Shengnan Hao, Haotian Wu, Yanyan Jiang, Zhanlin Ji, Li Zhao, Linyun Liu and Ivan Ganchev
Accurate segmentation of lesions can provide strong evidence for early skin cancer diagnosis by doctors, enabling timely treatment of patients and effectively reducing cancer mortality rates. In recent years, some deep learning models have utilized compl...
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Yu-Ming Zhang, Chia-Yuan Cheng, Chih-Lung Lin, Chun-Chieh Lee and Kuo-Chin Fan
Biometrics has become an important research issue in recent years, and the use of deep learning neural networks has made it possible to develop more reliable and efficient recognition systems. Palms have been identified as one of the most promising candi...
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Miao Feng and Jean Meunier
Recognizing human actions can help in numerous ways, such as health monitoring, intelligent surveillance, virtual reality and human?computer interaction. A quick and accurate detection algorithm is required for daily real-time detection. This paper first...
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