A Comprehensive Study of Camouflaged Object Detection Using Deep Learning

Abstract

Various living organisms and objects around us often blend themselves with their environment and is thus invisible to the naked eye. Whether it is an organism like a pygmy seahorse, a warfare tank or a soldier, the Camouflage Object Detection Using Deep Learning overcomes these issues of objects hiding within the environment. In addition to object detection, we detect camouflage objects within an image using deep learning techniques. Deep learning is a subset of machine learning that is essentially a three-layer neural network. Over 6500 images that possess camouflage properties are gathered from various internet sources and divided into four categories to compare the result. Those images are labeled and then trained and tested using VGG16 architecture. The architecture is further customized using transfer learning. The purpose of this transfer of learning methodologies is to aid in the evolution of machine learning to the point where it is as efficient as human learning.