Deep Autoencoder Model Construction Based on Pytorch

An image is a picture formed by the real existence of the outside world through the visual system of the brain. Since the image is the most intuitive thing that humans see and the easiest to understand, the image is the main means for people to obtain information from the outside world. The key work of image recognition is to explore the representation of the input image, and finally let the machine complete the understanding of the input image by itself, so as to recognize and classify it. Image processing processes externally input samples through machines, and filters out important features from the input images to realize image recognition and classification. Image recognition involves a wide range of research contents, such as license plate recognition, handwritten digit recognition, face recognition, recognition and classification of parts in machining, and accurate weather forecasting based on meteorological satellite photos. Among them, handwritten digit recognition mainly studies the digits handwritten by humans on paper, and uses machines to automatically complete the recognition and classification. Handwritten numbers are often encountered in our daily life, such as: manual bills, hand-filled express orders, and old-fashioned bank deposit slips, etc.