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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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Jianlong Ye, Hongchuan Yu, Gaoyang Liu, Jiong Zhou and Jiangpeng Shu
Component identification and depth estimation are important for detecting the integrity of post-disaster structures. However, traditional manual methods might be time-consuming, labor-intensive, and influenced by subjective judgments of inspectors. Deep-...
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Jee-Tae Park, Chang-Yui Shin, Ui-Jun Baek and Myung-Sup Kim
The classification of encrypted traffic plays a crucial role in network management and security. As encrypted network traffic becomes increasingly complicated and challenging to analyze, there is a growing need for more efficient and comprehensive analyt...
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Jie Zhang, Fan Li, Xin Zhang, Yue Cheng and Xinhong Hei
As a crucial task for disease diagnosis, existing semi-supervised segmentation approaches process labeled and unlabeled data separately, ignoring the relationships between them, thereby limiting further performance improvements. In this work, we introduc...
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Qiqi Zheng, Chao Wei, Xinfei Yan, Housong Ruan and Bangyu Wu
Seismic elastic parameter inversion translates seismic data into subsurface structures and physical properties of formations. Traditional model-based inversion methods have limitations in retrieving complex geological structures. In recent years, deep le...
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Qianmu Xiao and Liang Zhao
Acquiring relevant, high-quality, and heterogeneous medical images is essential in various types of automated analysis, used for a variety of downstream data augmentation tasks. However, a large number of real image samples are expensive to obtain, espec...
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Jing Tian, Zilin Zhao and Zhiming Ding
With the widespread use of the location-based social networks (LBSNs), the next point-of-interest (POI) recommendation has become an essential service, which aims to understand the user?s check-in behavior at the current moment by analyzing and mining th...
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Shi Li and Xiaoting Chen
The task of joint dialogue act recognition (DAR) and sentiment classification (DSC) aims to predict both the act and sentiment labels of each utterance in a dialogue. Existing methods mainly focus on local or global semantic features of the dialogue from...
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Jinya Xu, Jiaye Gong, Luyao Wang and Yunbo Li
The stability of navigation in waves is crucial for ships, and the effect of the waves on navigation stability is complicated. Hence, the LSTM neural network technique is applied to predict the course changing of a ship in different wave conditions, wher...
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Wentao Lv, Fan Li, Shijie Luo and Jie Xiang
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that can reduce quality of life and burden families. However, there is a lack of objectivity in clinical diagnosis, so it is very important to develop a method for early and accurate...
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