In the article, the authors examine the possibility of automatic localization of rice
fungal infections using modern methods of computer vision. The authors consider a new approach
based on the use of autoencoders - special neural network architectures. This approach makes it
possible to detect areas on rice leaves affected by a particular disease. The authors demonstrate
that the autoencoder can be trained to remove affected areas from the image. In some cases, this
allows one to clearly highlight the affected area by comparing the resulting image with the
original one. Therefore, modern architectures of convolutional autoencoders provide quite
acceptable visual quality of detection.