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Bin Li, Huazhong Lu, Xinyu Wei, Shixuan Guan, Zhenyu Zhang, Xingxing Zhou and Yizhi Luo
Accurate litchi identification is of great significance for orchard yield estimations. Litchi in natural scenes have large differences in scale and are occluded by leaves, reducing the accuracy of litchi detection models. Adopting traditional horizontal ...
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Sicong Liu, Qingcheng Fan, Chunjiang Zhao and Shuqin Li
Animal resources are significant to human survival and development and the ecosystem balance. Automated multi-animal object detection is critical in animal research and conservation and ecosystem monitoring. The objective is to design a model that mitiga...
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Fan Liu and Jiandong Fang
Classroom interactivity is one of the important metrics for assessing classrooms, and identifying classroom interactivity through classroom image data is limited by the interference of complex teaching scenarios. However, audio data within the classroom ...
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Hechao Ye and Yanni Wang
Crowding and occlusion pose significant challenges for pedestrian detection, which can easily lead to missed and false detections for small-scale and occluded pedestrian objects in dense pedestrian scenarios. To enhance dense pedestrian detection accurac...
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Yujia Zhang, Luteng Zhong, Yu Ding, Hongfeng Yu and Zhaoyu Zhai
Rice is a staple food for over half of the global population, but it faces significant yield losses: up to 52% due to leaf blast disease and brown spot diseases, respectively. This study aimed at proposing a hybrid architecture, namely ResViT-Rice, by ta...
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Zifan Rong, Xuesong Jiang, Linfeng Huang and Hongping Zhou
Pan-sharpening aims to create high-resolution spectrum images by fusing low-resolution hyperspectral (HS) images with high-resolution panchromatic (PAN) images. Inspired by the Swin transformer used in image classification tasks, this research constructs...
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Feng Zhang, Zhifeng Zhang, Sa Xiao, Kai Xie, Jiawei Ni, Haolun Gu, Yong Wu, Yang Ning and Qingchao Xia
The subsea observation network has become an indispensable means of ocean exploration worldwide. However, the scale of the subsea observation network is limited by the power supply voltage and power level. Hence, to promote the development of a subsea ob...
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Haiping Si, Mingchun Li, Weixia Li, Guipei Zhang, Ming Wang, Feitao Li and Yanling Li
Apples, as the fourth-largest globally produced fruit, play a crucial role in modern agriculture. However, accurately identifying apple diseases remains a significant challenge as failure in this regard leads to economic losses and poses threats to food ...
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Hui Luo, Lianming Cai and Chenbiao Li
As the operational time of the railway increases, rail surfaces undergo irreversible defects. Once the defects occur, it is easy for them to develop rapidly, which seriously threatens the safe operation of trains. Therefore, the accurate and rapid detect...
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Mingxuan Li, Ou Li, Guangyi Liu and Ce Zhang
Recently, automatic modulation recognition has been an important research topic in wireless communication. Due to the application of deep learning, it is prospective of using convolution neural networks on raw in-phase and quadrature signals in developin...
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Sijie Liu, Nan Zhou, Chenchen Song, Geng Chen and Yafeng Wu
This research introduces the Enhanced Scale-Aware efficient Transformer (ESAE-Transformer), a novel and advanced model dedicated to predicting Exhaust Gas Temperature (EGT). The ESAE-Transformer merges the Multi-Head ProbSparse Attention mechanism with t...
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Han Zhang, Yadong Wu, Weihan Zhang and Yuling Zhang
The precise ascertainment of stellar ages is pivotal for astrophysical research into stellar characteristics and galactic dynamics. To address the prevalent challenges of suboptimal accuracy in stellar age determination and limited proficiency in apprehe...
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Boyu Xie, Qi Su, Beilun Tang, Yan Li, Zhengwu Yang, Jiaoyang Wang, Chenxi Wang, Jingxian Lin and Lin Li
With the advancement in modern agricultural technologies, ensuring crop health and enhancing yield have become paramount. This study aims to address potential shortcomings in the existing chili disease detection methods, particularly the absence of optim...
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Chenglin Yang, Dongliang Xu and Xiao Ma
Due to the increasing severity of network security issues, training corresponding detection models requires large datasets. In this work, we propose a novel method based on generative adversarial networks to synthesize network data traffic. We introduced...
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Jin Peng, Chengming Liu, Haibo Pang, Xiaomeng Gao, Guozhen Cheng and Bing Hao
With the rise of image manipulation techniques, an increasing number of individuals find it easy to manipulate image content. Undoubtedly, this presents a significant challenge to the integrity of multimedia data, thereby fueling the advancement of image...
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Yaowei Feng, Zhendong Li, Dong Yang, Hongkai Hu, Hui Guo and Hao Liu
The segmentation of optic disc (OD) and optic cup (OC) are used in the automatic diagnosis of glaucoma. However, the spatially ambiguous boundary and semantically uncertain region-of-interest area in pictures may lead to the degradation of the performanc...
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Xintao Liang, Yuhang Li, Xiaomin Li, Yue Zhang and Youdong Ding
Implementing single-channel speech enhancement under unknown noise conditions is a challenging problem. Most existing time-frequency domain methods are based on the amplitude spectrogram, and these methods often ignore the phase mismatch between noisy sp...
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Zhongchang Ye, Xin Ye and Zhonghua Zhao
Intelligent video surveillance (IVS) technology is widely used in various security systems. However, quality degradation in surveillance images (SIs) may affect its performance on vision-based tasks, leading to the difficulties in the IVS system extracti...
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Roberto Pecoraro, Valerio Basile and Viviana Bono
Since the Transformer architecture was introduced in 2017, there has been many attempts to bring the self-attention paradigm in the field of computer vision. In this paper, we propose LHC: Local multi-Head Channel self-attention, a novel self-attention m...
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Santiago Pascual, Joan Serrà and Antonio Bonafonte
Conversion from text to speech relies on the accurate mapping from linguistic to acoustic symbol sequences, for which current practice employs recurrent statistical models such as recurrent neural networks. Despite the good performance of such models (in...
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