A novel method for data augmentation: Nine Dot Moving Least Square (ND-MLS)

no code implementations • 24 Aug 2022 • Wen Yang, Rui Wang, Yanchao Zhang

However, the ND-MLS method has stable performance and obtains 96. 5 top-1 acc in Res-Net on 100 different handwritten character classification tasks; 2) in segmentation, under the premise of only ten original images, DeepLab obtains 93. 5%, 85%, and 73. 3% m_IOU(10) on the bottle, horse, and grass test datasets, respectively, while the cat test dataset obtains 86. 7% m_IOU(10) with the SegNet model; 3) with only 10 original images from each category in object detection, YOLO v4 obtains 100% and 97. 2% bottle and horse detection, respectively, while the cat dataset obtains 93. 6% with YOLO v3.

Classification Data Augmentation +3