Investigating and Explaining the Frequency Bias in Image Classification

It is shown that one of which is the capability of employing before CNNs feature extraction, HOG[Surasak et al., 2018] high-frequency components. This paper discusses feature for all frequency components manifest noticeable the frequency bias phenomenon in image classification discrimination between classes. However, after CNNs feature tasks: the high-frequency components are actually extraction, while feature discrimination for the low-and much less exploited than the low-and midfrequency middle-frequency components (left two sub-figures) are enhanced components. We first investigate the frequency due to supervised learning, the high-frequency components bias phenomenon by presenting two observations (right two sub-figures) are considerably inhibited.