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Yimin Ma, Yi Xu, Yunqing Liu, Fei Yan, Qiong Zhang, Qi Li and Quanyang Liu
In recent years, deep convolutional neural networks with multi-scale features have been widely used in image super-resolution reconstruction (ISR), and the quality of the generated images has been significantly improved compared with traditional methods....
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Xiaoqin Xue, Chao Ren, Anchao Yin, Ying Zhou, Yuanyuan Liu, Cong Ding and Jiakai Lu
In the domain of remote sensing research, the extraction of roads from high-resolution imagery remains a formidable challenge. In this paper, we introduce an advanced architecture called PCCAU-Net, which integrates Pyramid Pathway Input, CoordConv convol...
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Zongshun Wang, Ce Li, Jialin Ma, Zhiqiang Feng and Limei Xiao
In this study, we introduce a novel framework for the semantic segmentation of point clouds in autonomous driving scenarios, termed PVI-Net. This framework uniquely integrates three different data perspectives?point clouds, voxels, and distance maps?exec...
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Guoqing Feng, Cheng Wang, Aichen Wang, Yuanyuan Gao, Yanan Zhou, Shuo Huang and Bin Luo
Crop lodging is an important cause of direct economic losses and secondary disease transmission in agricultural production. Most existing methods for segmenting wheat lodging areas use a large-volume network, which poses great difficulties for annotation...
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Chuan Xu, Qi Zhang, Liye Mei, Xiufeng Chang, Zhaoyi Ye, Junjian Wang, Lang Ye and Wei Yang
Road crack detection is one of the important issues in the field of traffic safety and urban planning. Currently, road damage varies in type and scale, and often has different sizes and depths, making the detection task more challenging. To address this ...
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Yundong Li, Xiaokun Wei and Hanlu Fan
Monocular depth estimation (MDE), as one of the fundamental tasks of computer vision, plays important roles in downstream applications such as virtual reality, 3D reconstruction, and robotic navigation. Convolutional neural networks (CNN)-based methods g...
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Xinyi Liu, Baofeng Zhang and Na Liu
Both transformer and one-stage detectors have shown promising object detection results and have attracted increasing attention. However, the developments in effective domain adaptive techniques in transformer and one-stage detectors still have not been w...
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Yanna Sang, Yuan Chen and Juwei Zhang
Neural machine translation has achieved good translation results, but needs further improvement in low-resource and domain-specific translation. To this end, the paper proposed to incorporate source language syntactic information into neural machine tran...
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Xueliang Wang, Nan Yang, Enjun Liu, Wencheng Gu, Jinglin Zhang, Shuo Zhao, Guijiang Sun and Jian Wang
In order to solve the problem of manual labeling in semi-supervised tree species classification, this paper proposes a pixel-level self-supervised learning model named M-SSL (multisource self-supervised learning), which takes the advantage of the informa...
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Mamatjan Abdurxit, Turdi Tohti and Askar Hamdulla
Biomedical entity linking is an important research problem for many downstream tasks, such as biomedical intelligent question answering, information retrieval, and information extraction. Biomedical entity linking is the task of mapping mentions in medic...
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