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Sundas Iftikhar, Muhammad Asim, Zuping Zhang, Ammar Muthanna, Junhong Chen, Mohammed El-Affendi, Ahmed Sedik and Ahmed A. Abd El-Latif
In smart cities, target detection is one of the major issues in order to avoid traffic congestion. It is also one of the key topics for military, traffic, civilian, sports, and numerous other applications. In daily life, target detection is one of the ch...
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Fei Yan, Hui Zhang, Yaogen Li, Yongjia Yang and Yinping Liu
Raw image classification datasets generally maintain a long-tailed distribution in the real world. Standard classification algorithms face a substantial issue because many labels only relate to a few categories. The model learning processes will tend tow...
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Yanmin Chen, Xiu Li, Mei Jia, Jiuliang Li, Tianyang Hu and Jun Luo
In order to achieve accurate segmentation of each grape image per berry, we construct a dataset composed of red globe grape samples and use a two-stage ?localization?segmentation? framework-based mask region convolutional neural network (Mask R-CNN) and ...
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Yuchao Wang, Jingdong Li, Zeming Chen and Chenglong Wang
In order to solve the problem of low accuracy of small target detection in traditional target detection algorithms, the YOLOX algorithm combined with Convolutional Block Attention Module (CBAM) is proposed. The algorithm first uses CBAM on the shallow fe...
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Ho-Won Lee, Kyong-Oh Lee, Ji-Hye Bae, Se-Yeob Kim and Yoon-Young Park
When an indoor disaster occurs, the disaster site can become very difficult to escape from due to the scenario or building. Most people evacuate when a disaster situation occurs, but there are also disaster victims who cannot evacuate and are isolated. I...
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