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Jingjing Liu, Jinkun Yang, Kexiu Liu and Lingyu Xu
Ocean current (OC) prediction plays an important role for carrying out ocean-related activities. There are plenty of studies for OC prediction with deep learning to pursue better prediction performance, and the attention mechanism was widely used for the...
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Haiyang Yao, Tian Gao, Yong Wang, Haiyan Wang and Xiao Chen
To overcome the challenges of inadequate representation and ineffective information exchange stemming from feature homogenization in underwater acoustic target recognition, we introduce a hybrid network named Mobile_ViT, which synergizes MobileNet and Tr...
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Zhou Fang, Xiaoyong Wang, Liang Zhang and Bo Jiang
Currently, deep learning is extensively utilized for ship target detection; however, achieving accurate and real-time detection of multi-scale targets remains a significant challenge. Considering the diverse scenes, varied scales, and complex backgrounds...
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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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Jing Luo, Yuhang Zhang, Jiayuan Zhuang and Yumin Su
The development of intelligent task allocation and path planning algorithms for unmanned surface vehicles (USVs) is gaining significant interest, particularly in supporting complex ocean operations. This paper proposes an intelligent hybrid algorithm tha...
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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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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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Ruoyang Li, Shuping Xiong, Yinchao Che, Lei Shi, Xinming Ma and Lei Xi
Semantic segmentation algorithms leveraging deep convolutional neural networks often encounter challenges due to their extensive parameters, high computational complexity, and slow execution. To address these issues, we introduce a semantic segmentation ...
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Zhanpeng Shi, Huantong Geng, Fangli Wu, Liangchao Geng and Xiaoran Zhuang
To solve the problems of the current deep learning radar extrapolation model consuming many resources and the final prediction result lacking details, a weather radar image super-resolution weather model based on SR3 (super-resolution via image restorati...
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Ping Huang and Yafeng Wu
Airborne speech enhancement is always a major challenge for the security of airborne systems. Recently, multi-objective learning technology has become one of the mainstream methods of monaural speech enhancement. In this paper, we propose a novel multi-o...
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Zheng Zhao, Jialing Yuan and Luhao Chen
Air Traffic Flow Management (ATFM) delay can quantitatively reflect the congestion caused by the imbalance between capacity and demand in an airspace network. Furthermore, it is an important parameter for the ex-post analysis of airspace congestion and t...
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Xuejun Yue, Haifeng Li, Qingkui Song, Fanguo Zeng, Jianyu Zheng, Ziyu Ding, Gaobi Kang, Yulin Cai, Yongda Lin, Xiaowan Xu and Chaoran Yu
Existing disease detection models for deep learning-based monitoring and prevention of pepper diseases face challenges in accurately identifying and preventing diseases due to inter-crop occlusion and various complex backgrounds. To address this issue, w...
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Chao He, Xinghua Zhang, Dongqing Song, Yingshan Shen, Chengjie Mao, Huosheng Wen, Dingju Zhu and Lihua Cai
With the popularization of better network access and the penetration of personal smartphones in today?s world, the explosion of multi-modal data, particularly opinionated video messages, has created urgent demands and immense opportunities for Multi-Moda...
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Yishen Lin, Zifan Huang, Yun Liang, Yunfan Liu and Weipeng Jiang
Citrus fruits hold pivotal positions within the agricultural sector. Accurate yield estimation for citrus fruits is crucial in orchard management, especially when facing challenges of fruit occlusion due to dense foliage or overlapping fruits. This study...
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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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Yaoqiang Pan, Xvlin Xiao, Kewei Hu, Hanwen Kang, Yangwen Jin, Yan Chen and Xiangjun Zou
In an unmanned orchard, various tasks such as seeding, irrigation, health monitoring, and harvesting of crops are carried out by unmanned vehicles. These vehicles need to be able to distinguish which objects are fruit trees and which are not, rather than...
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Hao An, Ruotong Ma, Yuhan Yan, Tailai Chen, Yuchen Zhao, Pan Li, Jifeng Li, Xinyue Wang, Dongchen Fan and Chunli Lv
This paper aims to address the increasingly severe security threats in financial systems by proposing a novel financial attack detection model, Finsformer. This model integrates the advanced Transformer architecture with the innovative cluster-attention ...
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Darian M. Onchis, Flavia Costi, Codruta Istin, Ciprian Cosmin Secasan and Gabriel V. Cozma
(1) Background: Lung cancers are the most common cancers worldwide, and prostate cancers are among the second in terms of the frequency of cancers diagnosed in men. Automatic ranking of the risk groups of such diseases is highly in demand, but the clinic...
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Yue Zha, Yuanzhi Ke, Xiao Hu and Caiquan Xiong
Named entity recognition (NER) is particularly challenging for medical texts due to the high domain specificity, abundance of technical terms, and sparsity of data in this field. In this work, we propose a novel attention layer, called the ?ontology atte...
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Zhao Xiong and Jiang Wu
Malaria is one of the major global health threats. Microscopic examination has been designated as the ?gold standard? for malaria detection by the World Health Organization. However, it heavily relies on the experience of doctors, resulting in long diagn...
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