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Jingxiong Lei, Xuzhi Liu, Haolang Yang, Zeyu Zeng and Jun Feng
High-resolution remote sensing images (HRRSI) have important theoretical and practical value in urban planning. However, current segmentation methods often struggle with issues like blurred edges and loss of detailed information due to the intricate back...
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Hang Li, Shengjie Zhao and Hao Deng
The extraction of community-scale green infrastructure (CSGI) poses challenges due to limited training data and the diverse scales of the targets. In this paper, we reannotate a training dataset of CSGI and propose a three-stage transfer learning method ...
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Zahra Ameli, Shabnam Jafarpoor Nesheli and Eric N. Landis
The application of deep learning (DL) algorithms has become of great interest in recent years due to their superior performance in structural damage identification, including the detection of corrosion. There has been growing interest in the application ...
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Yuhuan Wu and Yonghong Wu
Salient object detection (SOD) aims to identify the most visually striking objects in a scene, simulating the function of the biological visual attention system. The attention mechanism in deep learning is commonly used as an enhancement strategy which e...
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Yefeng Sun, Liang Gong, Wei Zhang, Bishu Gao, Yanming Li and Chengliang Liu
Drivable area detection is crucial for the autonomous navigation of agricultural robots. However, semi-structured agricultural roads are generally not marked with lanes and their boundaries are ambiguous, which impedes the accurate segmentation of drivab...
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Xinzhi Wang, Mengyue Li, Quanyi Liu, Yudong Chang and Hui Zhang
The accurate analysis of multi-scale flame development plays a crucial role in improving firefighting decisions and facilitating smart city establishment. However, flames? non-rigid nature and blurred edges present challenges in achieving accurate segmen...
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Tao Wang, Jingjing Chen, Li Liu and Lingling Guo
Recently, the deep learning technology has been adopted in the study of traditional village landscape. More precisely, it?s usually used to explore the representation of cultural heritage and the diversity of heritage information. In this study, we compr...
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Yu Guo, Guigen Nie, Wenliang Gao and Mi Liao
Semantic segmentation is a critical task in computer vision that aims to assign each pixel in an image a corresponding label on the basis of its semantic content. This task is commonly referred to as dense labeling because it requires pixel-level classif...
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Yongjiang Mao, Wenjuan Ren, Xipeng Li, Zhanpeng Yang and Wei Cao
With the progress of signal processing technology and the emergence of new system radars, the space electromagnetic environment becomes more and more complex, which puts forward higher requirements for the deinterleaving method of radar signals. Traditio...
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Joanna Kulawik, Mariusz Kubanek and Sebastian Garus
This research aimed to develop a system for classifying horizontal road signs as correct or with poor visibility. In Poland, road markings are applied by using a specialized white, reflective paint and require periodic repainting. Our developed system is...
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