Object Recognition on Long Range Thermal Image Using State of the Art DNN

This paper presents a method for detecting objects on long range thermal images. This problem is extremely complicated due to the low resolution of these images, and due to the fact that the objects that we want to detect have areas as small as 50 pixels. In order to solve this problem we have developed, trained and tested a large number (2640) of variations of the state of the art algorithm for visible camera object detection, called YOLO Darknet - You Only Look Once Darknet. The paper succeeds in showing that the deep neural network YOLO Darknet can be adapted to work on thermal images and, furthermore, it proves that the network is capable of detecting and classifying objects that are hard to detect with the human eye.