Imbalance Problems In Object Detection: A Review
Autor: | Kemal Oksuz, Baris Can Cam, Emre Akbas, Sinan Kalkan |
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Rok vydání: | 2021 |
Předmět: |
FOS: Computer and information sciences
business.industry Computer science Applied Mathematics Deep learning Computer Vision and Pattern Recognition (cs.CV) Computer Science - Computer Vision and Pattern Recognition 02 engineering and technology Data science Object detection Class imbalance Computational Theory and Mathematics Artificial Intelligence Taxonomy (general) Web page 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing The Internet Computer Vision and Pattern Recognition Artificial intelligence business Software Imbalance problems |
Popis: | In this paper, we present a comprehensive review of the imbalance problems in object detection. To analyze the problems in a systematic manner, we introduce a problem-based taxonomy. Following this taxonomy, we discuss each problem in depth and present a unifying yet critical perspective on the solutions in the literature. In addition, we identify major open issues regarding the existing imbalance problems as well as imbalance problems that have not been discussed before. Moreover, in order to keep our review up to date, we provide an accompanying webpage which catalogs papers addressing imbalance problems, according to our problem-based taxonomy. Researchers can track newer studies on this webpage available at: https://github.com/kemaloksuz/ObjectDetectionImbalance . Comment: Accepted to IEEE TPAMI; currently in press |
Databáze: | OpenAIRE |
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