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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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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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Zeyuan Zhao, Ping Li, Yongjie Dai, Zhaoe Min and Lei Chen
Alzheimer?s disease (AD) is an irreversible neurodegenerative disease. Providing trustworthy AD progression predictions for at-risk individuals contributes to early identification of AD patients and holds significant value in discovering effective treatm...
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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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Turdi Tohti, Mamatjan Abdurxit and Askar Hamdulla
Intent classification and named entity recognition of medical questions are two key subtasks of the natural language understanding module in the question answering system. Most existing methods usually treat medical queries intent classification and name...
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Reza Soleimani and Edgar Lobaton
Physiological and kinematic signals from humans are often used for monitoring health. Several processes of interest (e.g., cardiac and respiratory processes, and locomotion) demonstrate periodicity. Training models for inference on these signals (e.g., d...
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Minh-Trieu Tran, Soo-Hyung Kim, Hyung-Jeong Yang and Guee-Sang Lee
Distorted medical images can significantly hamper medical diagnosis, notably in the analysis of Computer Tomography (CT) images and organ segmentation specifics. Therefore, improving diagnostic imagery accuracy and reconstructing damaged portions are imp...
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Duc-Ky Ngo, Minh-Trieu Tran, Soo-Hyung Kim, Hyung-Jeong Yang and Guee-Sang Lee
Segmenting brain tumors accurately and reliably is an essential part of cancer diagnosis and treatment planning. Brain tumor segmentation of glioma patients is a challenging task because of the wide variety of tumor sizes, shapes, positions, scanning mod...
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Zhizhong Kang, Juntao Yang, Zhou Yang and Sai Cheng
Indoor environment model reconstruction has emerged as a significant and challenging task in terms of the provision of a semantically rich and geometrically accurate indoor model. Recently, there has been an increasing amount of research related to indoo...
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