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Maxim Bakaev, Sebastian Heil and Martin Gaedke
Training data for user behavior models that predict subjective dimensions of visual perception are often too scarce for deep learning methods to be applicable. With the typical datasets in HCI limited to thousands or even hundreds of records, feature-bas...
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Zhuoran Jiang, Xinxin Zhou, Wei Cao, Zaihong Sun and Changbin Wu
In recent years, deep learning has become the mainstream development direction in the change-detection field, and its accuracy and speed have also reached a high level. However, the change-detection method based on deep learning cannot predict all the ch...
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Ruifeng Luo, Yifan Wang, Weifang Xiao and Xianzhong Zhao
Truss layout optimization under complex constraints has been a hot and challenging problem for decades that aims to find the optimal node locations, connection topology between nodes, and cross-sectional areas of connecting bars. Monte Carlo Tree Search ...
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Wenzhuo Zhang, Mingyang Yu, Xiaoxian Chen, Fangliang Zhou, Jie Ren, Haiqing Xu and Shuai Xu
Deep learning technology, such as fully convolutional networks (FCNs), have shown competitive performance in the automatic extraction of buildings from high-resolution aerial images (HRAIs). However, there are problems of over-segmentation and internal c...
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Mirela Kundid Vasic and Vladan Papic
Recent results in person detection using deep learning methods applied to aerial images gathered by Unmanned Aerial Vehicles (UAVs) have demonstrated the applicability of this approach in scenarios such as Search and Rescue (SAR) operations. In this pape...
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