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Xing Yi, Hao Pan, Huaici Zhao, Pengfei Liu, Canyu Zhang, Junpeng Wang and Hao Wang
Image generation technology is currently one of the popular directions in computer vision research, especially regarding infrared imaging, bearing critical applications in the military field. Existing algorithms for generating infrared images from visibl...
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Bilal Ahmed Chandio, Ali Shariq Imran, Maheen Bakhtyar, Sher Muhammad Daudpota and Junaid Baber
Deep neural networks have emerged as a leading approach towards handling many natural language processing (NLP) tasks. Deep networks initially conquered the problems of computer vision. However, dealing with sequential data such as text and sound was a n...
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Yong Liu, Jialin Zhou, Dong Zhang, Shaoyu Wei, Mingshun Yang and Xinqin Gao
To solve the problem of low diagnostic accuracy caused by the scarcity of fault samples and class imbalance in the fault diagnosis task of box-type substations, a fault diagnosis method based on self-attention improvement of conditional tabular generativ...
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Shubin Wang, Yuanyuan Chen and Zhang Yi
The structure and function of retinal vessels play a crucial role in diagnosing and treating various ocular and systemic diseases. Therefore, the accurate segmentation of retinal vessels is of paramount importance to assist a clinical diagnosis. U-Net ha...
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Jun Peng and Baohua Su
The task of aspect-based sentiment analysis (ASBA) is to identify all the sentiment analyses expressed by specific aspect words in the text. How to identify specific objects (i.e., aspect words), describe the modifiers of the specific objects (i.e., opin...
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Chunchang Zhang and Ji Zeng
The real-time transmission of ship status data from vessels to shore is crucial for live status monitoring and guidance. Traditional reliance on expensive maritime satellite systems for this purpose is being reconsidered with the emergence of the global ...
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Giorgio Lazzarinetti, Riccardo Dondi, Sara Manzoni and Italo Zoppis
Solving combinatorial problems on complex networks represents a primary issue which, on a large scale, requires the use of heuristics and approximate algorithms. Recently, neural methods have been proposed in this context to find feasible solutions for r...
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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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Sen Xue, Chengyu Wu, Jing Han and Ao Zhan
How to select the transmitting path in MPTCP scheduling is an important but open problem. This paper proposes an intelligent data scheduling algorithm using spatiotemporal synchronous graph attention neural networks to improve MPTCP scheduling. By exploi...
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Guoying Wang, Jiafeng Ai, Lufeng Mo, Xiaomei Yi, Peng Wu, Xiaoping Wu and Linjun Kong
Anomaly detection has an important impact on the development of unmanned aerial vehicles, and effective anomaly detection is fundamental to their utilization. Traditional anomaly detection discriminates anomalies for single-dimensional factors of sensing...
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Tingyao Jiang, Wei Sun and Min Wang
Sentence-level sentiment analysis, as a research direction in natural language processing, has been widely used in various fields. In order to address the problem that syntactic features were neglected in previous studies on sentence-level sentiment anal...
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Hong-Hua Huang, Jian-Fei Luo, Feng Gan and Philip K. Hopke
Small data sets make developing calibration models using deep neural networks difficult because it is easy to overfit the system. We developed two deep neural network architectures by revising two existing network architectures: the U-Net and the attenti...
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Hua Yang, Shuxiang Zhang, Hao Shen, Gexiang Zhang, Xingquan Deng, Jianglin Xiong, Li Feng, Junxiong Wang, Haifeng Zhang and Shenyang Sheng
Text classification is one of the fundamental tasks in natural language processing and is widely applied in various domains. CNN effectively utilizes local features, while the Attention mechanism performs well in capturing content-based global interactio...
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Wei Liu, Junxing Cao, Jiachun You and Haibo Wang
Vector decomposition of P- and S-wave modes from elastic seismic wavefields is a key step in elastic reverse-time migration (ERTM) to effectively improve the multi-wave imaging accuracy. Most previously developed methods based on the apparent velocities ...
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Jiaqi Liu, Jian Sun and Xiao Qi
With the aim of promoting energy conservation and emission reduction, electric vehicles (EVs) have gained significant attention as a strategic industry in many countries. However, the insufficiency of accessible charging infrastructure remains a challeng...
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Xin Fang, Tong Zhen and Zhihui Li
Wheat disease detection is crucial for disease diagnosis, pesticide application optimization, disease control, and wheat yield and quality improvement. However, the detection of wheat diseases is difficult due to their various types. Detecting wheat dise...
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Zhihong Chang, Chunsheng Liu and Jianmin Jia
As an important component of intelligent transportation-management systems, accurate traffic-parameter prediction can help traffic-management departments to conduct effective traffic management. Due to the nonlinearity, complexity, and dynamism of highwa...
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Weiwei Sun, Shengquan Liu, Yan Liu, Lingqi Kong and Zhaorui Jian
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Jiawei Kang, Shangwen Yang, Xiaoxuan Shan, Jie Bao and Zhao Yang
Exploring the delay causality between airports and comparing the delay propagation patterns across different airport networks is critical to better understand delay propagation mechanisms and provide effective delay mitigation strategies. A novel attenti...
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Zhihao Liao, Neng Fan and Kai Xu
The proposed Swin-PANet can be utilized for computer-aided diagnosis (CAD) of skin cancer or cell cancer to improve the segmentation efficiency and accuracy, considered as a significant technique for the accurate screening of diseased or abnormal area of...
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