A Systematic Review of Species Classification Using Deep Learning Algorithms and Gender Identification of

Machine learning (ML) constitutes a division of artificial intelligence (AI) that aims to train computers how to perform specific tasks without explicit programming. Traditional ML tools are widely used for classification and identification of animals. However, these methods have some drawbacks because of the extensive manual reliance and the delay in data interpretation. To overcome this, Applied Deep Learning algorithms are used with Artificial Neural Networks (ANN) and Convolution Neural Network (CNN) models introduced to address species classification, characteristics detection, and pattern recognition tasks helping in accurate identification and classification of animals. In this paper, we have tried to compile and deliver a recent comprehensive information on latest available investigations in the field of life sciences particularly used for animal identification. We have also accentuated the diverse applications of machine learning models including other parameters like, features, accuracy gained, database used and their limitations. The red flour beetle,