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Lexin Zhang, Kuiheng Chen, Liping Zheng, Xuwei Liao, Feiyu Lu, Yilun Li, Yuzhuo Cui, Yaze Wu, Yihong Song and Shuo Yan
This study introduces a novel high-accuracy fruit fly detection model based on the Transformer structure, specifically aimed at addressing the unique challenges in fruit fly detection such as identification of small targets and accurate localization agai...
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Sai Wang, Guoping Fu, Yongduo Song, Jing Wen, Tuanqi Guo, Hongjin Zhang and Tuantuan Wang
The development of intelligent oceans requires exploration and an understanding of the various characteristics of the oceans. The emerging Internet of Underwater Things (IoUT) is an extension of the Internet of Things (IoT) to underwater environments, an...
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Wei Zhuang, Zhiheng Li, Ying Wang, Qingyu Xi and Min Xia
Predicting photovoltaic (PV) power generation is a crucial task in the field of clean energy. Achieving high-accuracy PV power prediction requires addressing two challenges in current deep learning methods: (1) In photovoltaic power generation prediction...
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Fatma Yaprakdal and Merve Varol Arisoy
In the smart grid paradigm, precise electrical load forecasting (ELF) offers significant advantages for enhancing grid reliability and informing energy planning decisions. Specifically, mid-term ELF is a key priority for power system planning and operati...
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Yuhao Lai, Ruijun Ma, Yu Chen, Tao Wan, Rui Jiao and Huandong He
The accurate detection of pineapples of different maturity levels in a complex field environment is the key step to achieving the early yield estimation and mechanized picking of pineapple. This study proposes a target detection model based on the improv...
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Jiahui Qian, Wenjun Xia, Zhangyan Zhao and Faju Qiu
Due to uncontrollable influences of the manufacturing process and different construction environments, there are significant challenges to extracting accurate positioning points for the lifting holes in prefabricated beams. In this study, we propose a tw...
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Xin Yuan, Shutong Fang, Ning Li, Qiansheng Ma, Ziheng Wang, Mingfeng Gao, Pingpeng Tang, Changli Yu, Yihan Wang and José-Fernán Martínez Ortega
Sea cucumber detection represents an important step in underwater environmental perception, which is an indispensable part of the intelligent subsea fishing system. However, water turbidity decreases the clarity of underwater images, presenting a challen...
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Thilo Reich, David Hulbert and Marcin Budka
This study presents a working concept of a model architecture allowing to leverage the state of an entire transport network to make estimated arrival time (ETA) and next-step location predictions. To this end, a combination of an attention mechanism with...
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Vladimir Skripachev,Mikhail Guida,Nikolay Guida,Alexander Zhukov
Pág. 53 - 61
The article discusses in detail the use of collapsible neural networks (CNNs) for use in solving problems of detecting objects in aerospace images. The structure of collapsing neural networks is revealed, taking into account the specifics of the applicat...
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Pin Wu, Rukang Zhu and Zhidan Lei
Using the single premise entailment (SPE) model to accomplish the multi-premise entailment (MPE) task can alleviate the problem that the neural network cannot be effectively trained due to the lack of labeled multi-premise training data. Moreover, the ab...
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