A machine learning-based silent living body image recognition method, comprising: obtaining an image to be verified; constructing multi-channel image data of said image according to color information and brightness information of said image; inputting the multi-channel image data into a preset deep convolutional network to obtain a feature tag corresponding to the multi-channel image data; and if the feature tag matches a target tag, determining said image as a living body image.
SILENT LIVING BODY IMAGE RECOGNITION METHOD AND APPARATUS, COMPUTER DEVICE AND STORAGE MEDIUM