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Zongcheng Yue, Chun-Yan Lo, Ran Wu, Longyu Ma and Chiu-Wing Sham
In urban environments, semantic segmentation using computer vision plays a pivotal role in understanding and interpreting the diverse elements within urban imagery. The Cityscapes dataset, widely used for semantic segmentation in urban scenes, predominan...
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Xuejing Xie, Yongyang Xu, Bin Feng and Wenjun Wu
The classification of urban functional areas is important for understanding the characteristics of urban areas and optimizing the utilization of urban land resources. Existing related methods have improved accuracy. However, they neglect cognitive differ...
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Jiale Qian, Yunyan Du, Fuyuan Liang, Jiawei Yi, Nan Wang, Wenna Tu, Sheng Huang, Tao Pei and Ting Ma
Understanding the public?s diverse linguistic expressions about rainfall and flood provides a basis for flood disaster studies and enhances linguistic and cultural awareness. However, existing research tends to overlook linguistic complexity, potentially...
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Eike Blomeier, Sebastian Schmidt and Bernd Resch
In the early stages of a disaster caused by a natural hazard (e.g., flood), the amount of available and useful information is low. To fill this informational gap, emergency responders are increasingly using data from geo-social media to gain insights fro...
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Zhendong He, Wenbin Yang, Yanjie Liu, Anping Zheng, Jie Liu, Taishan Lou and Jie Zhang
Ensuring the safety of transmission lines necessitates effective insulator defect detection. Traditional methods often need more efficiency and accuracy, particularly for tiny defects. This paper proposes an innovative insulator defect recognition method...
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Retno Kusumaningrum, Selvi Fitria Khoerunnisa, Khadijah Khadijah and Muhammad Syafrudin
The mangrove ecosystem is crucial for addressing climate change and supporting marine life. To preserve this ecosystem, understanding community awareness is essential. While latent Dirichlet allocation (LDA) is commonly used for this, it has drawbacks su...
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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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Xingxing Tong, Ming Chen and Guofu Feng
The issue of aquatic product quality and safety has gradually become a focal point of societal concern. Analyzing textual comments from people about aquatic products aids in promptly understanding the current sentiment landscape regarding the quality and...
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Abderrazzaq Kharroubi, Zouhair Ballouch, Rafika Hajji, Anass Yarroudh and Roland Billen
Railway scene understanding is crucial for various applications, including autonomous trains, digital twining, and infrastructure change monitoring. However, the development of the latter is constrained by the lack of annotated datasets and limitations o...
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Shuo Chen, Hartmut Helmke, Robert M. Tarakan, Oliver Ohneiser, Hunter Kopald and Matthias Kleinert
As researchers around the globe develop applications for the use of Automatic Speech Recognition and Understanding (ASRU) in the Air Traffic Management (ATM) domain, Air Traffic Control (ATC) language ontologies will play a critical role in enabling rese...
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