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Keyword: Mosaic data augmentation ×Clear all

1 claim from 1 paper

1. Computer Science › Advanced Neural Network Applications

   YOLOv4: Optimal Speed and Accuracy of Object Detection

   Bochkovskiy, Wang and Liao · arXiv (Cornell University) · 2020

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   1. UncheckedYOLOv4 combines several new training and network techniques to reach 43.5% AP on MS COCO at about 65 frames per second on a Tesla V100.“We use new features: WRC, CSP, CmBN, SAT, Mish activation, Mosaic data augmentation, CmBN, DropBlock regularization, and CIoU loss, and combine some of them to achieve state-of-the-art results: 43.5% AP (65.7% AP50) for the MS COCO dataset at a realtime speed of ~65 FPS on Tesla V100.”