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Jingyi Hu, Junfeng Guo, Zhiyuan Rui and Zhiming Wang
To solve the problem that noise seriously affects the online monitoring of parts signals of outdoor machinery, this paper proposes a signal reconstruction method integrating deep neural network and compression sensing, called ADMM-1DNet, and gives a deta...
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Qiyan Li, Zhi Weng, Zhiqiang Zheng and Lixin Wang
The decrease in lake area has garnered significant attention within the global ecological community, prompting extensive research in remote sensing and computer vision to accurately segment lake areas from satellite images. However, existing image segmen...
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Che-Hao Chang, Jason Lin, Jia-Wei Chang, Yu-Shun Huang, Ming-Hsin Lai and Yen-Jen Chang
Recently, data-driven approaches have become the dominant solution for prediction problems in agricultural industries. Several deep learning models have been applied to crop yield prediction in smart farming. In this paper, we proposed an efficient hybri...
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Junyi Chen, Yanyun Shen, Yinyu Liang, Zhipan Wang and Qingling Zhang
Aircraft detection in SAR images of airports remains crucial for continuous ground observation and aviation transportation scheduling in all weather conditions, but low resolution and complex scenes pose unique challenges. Existing methods struggle with ...
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Jih-Ching Chiu, Guan-Yi Lee, Chih-Yang Hsieh and Qing-You Lin
In computer vision and image processing, the shift from traditional cameras to emerging sensing tools, such as gesture recognition and object detection, addresses privacy concerns. This study navigates the Integrated Sensing and Communication (ISAC) era,...
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Omar Serghini, Hayat Semlali, Asmaa Maali, Abdelilah Ghammaz and Salvatore Serrano
Spectrum sensing is an essential function of cognitive radio technology that can enable the reuse of available radio resources by so-called secondary users without creating harmful interference with licensed users. The application of machine learning tec...
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Dong Jiang, Wenji Zhao, Yanhui Wang and Biyu Wan
Traffic congestion is a globally widespread problem that causes significant economic losses, delays, and environmental impacts. Monitoring traffic conditions and analyzing congestion factors are the first, challenging steps in optimizing traffic congesti...
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Zhou Fang, Xiaoyong Wang, Liang Zhang and Bo Jiang
Currently, deep learning is extensively utilized for ship target detection; however, achieving accurate and real-time detection of multi-scale targets remains a significant challenge. Considering the diverse scenes, varied scales, and complex backgrounds...
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Lun-Min Shih, Huan-Liang Tsai and Cheng-Yu Tsai
This paper presents an original wireless DYU Air Box of an environment-monitoring IoT (EMIoT) system on a campus to offer information on environmental conditions through the public ThingSpeak IoT platform for stakeholders including all the students and e...
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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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