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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 ...
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Yifan Shang, Wanneng Yu, Guangmiao Zeng, Huihui Li and Yuegao Wu
Image recognition is vital for intelligent ships? autonomous navigation. However, traditional methods often fail to accurately identify maritime objects? spatial positions, especially under electromagnetic silence. We introduce the StereoYOLO method, an ...
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Ping Dong, Kuo Li, Ming Wang, Feitao Li, Wei Guo and Haiping Si
In addition to the conventional situation of detecting a single disease on a single leaf in corn leaves, there is a complex phenomenon of multiple diseases overlapping on a single leaf (compound diseases). Current research on corn leaf disease detection ...
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Alvaro A. Teran-Quezada, Victor Lopez-Cabrera, Jose Carlos Rangel and Javier E. Sanchez-Galan
Convolutional neural networks (CNN) have provided great advances for the task of sign language recognition (SLR). However, recurrent neural networks (RNN) in the form of long?short-term memory (LSTM) have become a means for providing solutions to problem...
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Priyank Kalgaonkar and Mohamed El-Sharkawy
Accurate perception is crucial for autonomous vehicles (AVs) to navigate safely, especially in adverse weather and lighting conditions where single-sensor networks (e.g., cameras or radar) struggle with reduced maneuverability and unrecognizable targets....
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Yiming Mo, Lei Wang, Wenqing Hong, Congzhen Chu, Peigen Li and Haiting Xia
The intrusion of foreign objects on airport runways during aircraft takeoff and landing poses a significant safety threat to air transportation. Small-scale Foreign Object Debris (FOD) cannot be ruled out on time by traditional manual inspection, and the...
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Yuchen Dong, Heng Zhou, Chengyang Li, Junjie Xie, Yongqiang Xie and Zhongbo Li
Camouflaged object detection (COD) is an arduous challenge due to the striking resemblance of camouflaged objects to their surroundings. The abundance of similar background information can significantly impede the efficiency of camouflaged object detecti...
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Junsheng Liu, Guangze Zhao, Shuangxi Liu, Yi Liu, Huawei Yang, Jingwei Sun, Yinfa Yan, Guoqiang Fan, Jinxing Wang and Hongjian Zhang
In the realm of automated apple picking operations, the real-time monitoring of apple maturity and diameter characteristics is of paramount importance. Given the constraints associated with feature detection of apples in automated harvesting, this study ...
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JongBae Kim
This technology can prevent accidents involving large vehicles, such as trucks or buses, by selecting an optimal driving lane for safe autonomous driving. This paper proposes a method for detecting forward-driving vehicles within road images obtained fro...
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Huizhong Xiong, Xiaotong Gao, Ningyi Zhang, Haoxiong He, Weidong Tang, Yingqiu Yang, Yuqian Chen, Yang Jiao, Yihong Song and Shuo Yan
A novel deep learning model, DiffuCNN, is introduced in this paper, specifically designed for counting tobacco lesions in complex agricultural settings. By integrating advanced image processing techniques with deep learning methodologies, the model signi...
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