A Deep Learning Approach for Detection and Classification of Ten Species of Monkeys

The IUCN's Red List of Endangered Species has recently classified several monkey species as vulnerable or endangered due to the decline in indigenous populations of different monkey species, such as Mantled Howlers, Patas Monkeys, and Bald Uakari. It has become crucial to monitor and manage these incredible creatures for their protection owing to habitat devastation brought on by either direct or indirect human activities like industrialization, poaching, and hunting. Based on ten distinct monkey species' images, a CNN model has been proposed in this research for their identification and categorization. 1370 images were utilized for training and 272 images were utilized for testing the model. The proposed CNN model used fully connected layers for the final classification after several layers of convolutional and pooling procedures. The model's 81% accuracy rate for the image classification task on the test set shows the value of DL methods for classifying different species of animals. By offering an automated and precise approach to identifying different kinds of monkeys, the proposed CNN model can assist with the conservation of various monkey species. Monitoring animal population levels, distributions, and behaviors depends on identifying and categorizing different species. It can also help recognize these creatures' dangers and threats, allowing conservation efforts to be more effectively focused.