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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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Tahir Mehmood, Ivan Serina, Alberto Lavelli, Luca Putelli and Alfonso Gerevini
Biomedical named entity recognition (BioNER) is a preliminary task for many other tasks, e.g., relation extraction and semantic search. Extracting the text of interest from biomedical documents becomes more demanding as the availability of online data is...
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Tahir Mehmood, Alfonso E. Gerevini, Alberto Lavelli, Matteo Olivato and Ivan Serina
Single-task models (STMs) struggle to learn sophisticated representations from a finite set of annotated data. Multitask learning approaches overcome these constraints by simultaneously training various associated tasks, thereby learning generic represen...
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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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Xiaoping Huang, Yujian Zhou and Yajun Du
In recent years, there has been rapid development in machine learning for solving artificial intelligence tasks in various fields, including translation, speech, and image processing. These AI tasks are often interconnected rather than independent. One s...
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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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