Accuracy analysis of deep learning–driven image recognition through graph models of thermal sensing networks

[Abstract] This paper aims to discuss the accuracy analysis of image recognition system based on deep learning algorithm and infrared thermal sensing. This paper expounds the basic principle and implementation of deep learning algorithm, and verifies its effectiveness through a series of experimental tests. Combining the advantages of cloud computing platform, a novel cloud computing image recognition system is designed, which makes full use of the characteristics of infrared thermal image data to train and optimize deep learning algorithms. The results show that the infrared thermal sensor image recognition system based on deep learning has significant advantages in precision analysis, the recognition rate is higher than the traditional algorithm, and it shows superior robustness in a variety of environments. The accuracy analysis shows that the cloud computing technology can effectively improve the processing capacity of the system, and further improve the efficiency and accuracy of image recognition.