Multi-source unsupervised domain adaptation for object detection

Dan Zhang; Mao Ye; Yiguang Liu; Lin Xiong; Lihua Zhou

doi:10.1016/j.inffus.2021.09.011

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JOURNAL ARTICLE

Multi-source unsupervised domain adaptation for object detection

Dan Zhang Mao Ye Yiguang Liu Lin Xiong Lihua Zhou

Year: 2021 Journal: Information Fusion Vol: 78 Pages: 138-148 Publisher: Elsevier BV

DOI: 10.1016/j.inffus.2021.09.011

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Keywords:

Computer science Leverage (statistics) Pattern recognition (psychology) Artificial intelligence Transfer of learning Feature (linguistics) Domain (mathematical analysis) Domain adaptation Feature extraction Object detection Multi-source Sample (material) Data mining Classifier (UML) Mathematics

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Domain Adaptation and Few-Shot Learning

Physical Sciences → Computer Science → Artificial Intelligence

Advanced Neural Network Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Image and Video Retrieval Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Multi-source unsupervised domain adaptation for object detection

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