Retinanet Deep Learning-Based Approach to Detect Termite Mounds in Eucalyptus Forests

Brazilian eucalyptus plantations are largely used to produce wood products and play an important role in the country's economy. The presence of termites in these plantations can cause serious damage, requiring their identification and control. Here, we investigated the RetinaNet object detection deep learning method's potential to identify termite mounds in eucalyptus forests automatically. The experiments were conducted using terrestrial images acquired with a GoPro 360, composed of two fisheye cameras, providing a challenging task due to non-conventional geometry. In the tests, the model presented an Average Precision (AP) of 0.721, and after stipulating thresholds from which the objects would be used in training, the AP was 0.867.