UDC 681.3
DOI: 10.36871/2618-9976.2022.08.002
Authors
Ivan A. Logachevsky
Director General
Abstract
The equipment of thermal stations and heating networks, which is subject to corrosion and is often far from new, loses its original characteristics over time. Such processes, potentially leading to heat losses and coolant leaks, can lead to significant financial and environmental consequences. Infrared thermography is one of the effective problemsolving methods that helps to detect defects and reduce risks. This article discusses some details of the current project for the analysis of thermal images using convolutional neural networks.
Keywords
Thermal images, Thermal imager, Convolutional neural network, Neural network model, Neural network analysis, Semantic segmentation
