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Adam Olesinski and Zbigniew Piotrowski
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MohammadHossein Reshadi, Wen Li, Wenjie Xu, Precious Omashor, Albert Dinh, Scott Dick, Yuntong She and Michael Lipsett
Anomaly detection in data streams (and particularly time series) is today a vitally important task. Machine learning algorithms are a common design for achieving this goal. In particular, deep learning has, in the last decade, proven to be substantially ...
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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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Kui Zeng, Shutan Xu, Daode Shu and Ming Chen
Medaka (Oryzias latipes), as a crucial model organism in biomedical research, holds significant importance in fields such as cardiovascular diseases. Currently, the analysis of the medaka ventricle relies primarily on visual observation under a microscop...
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Xuefeng Zhang, Youngsung Kim, Young-Chul Chung, Sangcheol Yoon, Sang-Yong Rhee and Yong Soo Kim
Large-scale datasets, which have sufficient and identical quantities of data in each class, are the main factor in the success of deep-learning-based classification models for vision tasks. A shortage of sufficient data and interclass imbalanced data dis...
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