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Viktoriya Tsyganskaya, Sandro Martinis and Philip Marzahn
Synthetic Aperture Radar (SAR) is particularly suitable for large-scale mapping of inundations, as this tool allows data acquisition regardless of illumination and weather conditions. Precise information about the flood extent is an essential foundation ...
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Jerry Gao, Charanjit Kaur Bambrah, Nidhi Parihar, Sharvaree Kshirsagar, Sruthi Mallarapu, Hailong Yu, Jane Wu and Yunyun Yang
With the development of artificial intelligence, the intelligence of agriculture has become a trend. Intelligent monitoring of agricultural activities is an important part of it. However, due to difficulties in achieving a balance between quality and cos...
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Yujuan Cao, Jianguo Dai, Guoshun Zhang, Minghui Xia and Zhitan Jiang
This paper combines feature selection with machine learning algorithms to achieve object-oriented classification of crops in Gaofen-6 remote sensing images. The study provides technical support and methodological references for research on regional monit...
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Youngkwang Kim, Woochan Kim, Jungwoo Yoon, Sangkug Chung and Daegeun Kim
This paper presents a practical contamination detection system for camera lenses using image analysis with deep learning. The proposed system can detect contamination in camera digital images through contamination learning utilizing deep learning, and it...
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Hui Deng, Wenjiang Zhang, Xiaoqian Zheng and Houxi Zhang
The accurate and timely identification of crops holds paramount significance for effective crop management and yield estimation. Unmanned aerial vehicle (UAV), with their superior spatial and temporal resolution compared to satellite-based remote sensing...
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Xinwei Lyu, Xinjia Li, Yuexin Zhang and Wenlian Lu
The rapid expansion of e-commerce, particularly in the clothing sector, has led to a significant demand for an effective clothing industry. This study presents a novel two-stage image recognition method. Our approach distinctively combines human keypoint...
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Weiming Fan, Jiahui Yu and Zhaojie Ju
Endoscopy, a pervasive instrument for the diagnosis and treatment of hollow anatomical structures, conventionally necessitates the arduous manual scrutiny of seasoned medical experts. Nevertheless, the recent strides in deep learning technologies proffer...
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Tushar Ganguli and Edwin K. P. Chong
We present a novel technique for pruning called activation-based pruning to effectively prune fully connected feedforward neural networks for multi-object classification. Our technique is based on the number of times each neuron is activated during model...
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JongBae Kim
This technology can prevent accidents involving large vehicles, such as trucks or buses, by selecting an optimal driving lane for safe autonomous driving. This paper proposes a method for detecting forward-driving vehicles within road images obtained fro...
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Aileen C. Benedict and Zbigniew W. Ras
The paper concerns the problem of action-rule extraction when datasets are large. Such rules can be used to construct a knowledge base in a recommendation system. One of the popular approaches to construct action rules in such cases is to partition the d...
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