This work presents the development of a neural network model for detecting volcanic clouds under challenging conditions, where the cloud contains not only ash but also sulfur dioxide and ice. The presence of ice complicates detection and often leads to failures in traditional methods. Our results show that the neural network improves detection performance and supports the automatic volcanic cloud monitoring, which is crucial for aviation safety.