Monkey Features Location Identification Using Convolutional Neural Networks
Rollyn Labuguen (P), Vishal Gaurav, Salvador Negrete Blanco, Jumpei MatsumotoiD, Kenichi InoueiD, Tomohiro ShibataiD
Abstract
Understanding animal behavior in its natural habitat is a challenging task. One of the primary step for analyzing animal behavior is feature detection. In this study, we propose the use of deep convolutional neural network (CNN) to locate monkey features from raw RGB images of monkey in its natural environment. We train the model to identify features such as the nose and shoulders of the monkey at about 0.01 model loss.
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