A dissected dataset for single and double wildlife fences in South Africa
Description
The dataset consists of 211 images collected using a standalone camera and a drone, stored in jpeg format with a height and width of 512 and 512 pixels, respectively. The image dataset contains 105 single fences and 106 double fences. The drone camera images included 26 single fences and 26 double fence images. In contrast, the standalone camera has 159 images with 79 single and 80 double fences. We labeled the datasets as either still or aerial datasets. The still dataset contains only images that used a standalone camera; the drone captured aerial images of wildlife fences and scenes from the sky. The images can be used to develop deep learning algorithms that classify whether a wildlife fence is single or double. This study uses wildlife electric fences for both single and double. When machine learning algorithms detect electric fences, dangerous animals, such as lions, are in the game reserve, and road users expect to take extra precautions while using the road. In addition, the double fence ensures high double protection in case of failure of the inner fence to protect wildlife from escaping.