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Image and Feature Space Based Domain Adaptation for Vehicle Detection
Computers Materials & Continua
The application of deep learning in the field of object detection has experienced much progress. However, due to the domain shift problem, applying an off-the-shelf detector to another domain leads to a significant performance drop. A large number of ground truth labels are required when using another domain to train models, demanding a large amount of human and financial resources. In order to avoid excessive resource requirements and performance drop caused by domain shift, this paperdoi:10.32604/cmc.2020.011386 fatcat:l3lfk74tkrdjvggfld7xx7xfr4