Wildlife Classification Model - Deep Learning in Python with Keras

Mohammed Zidan Vaheed , Dr. M.N. Nachappa

Artificial Intelligence, Computer vision, Power heavy, Convolution Neural Networks, Class weights, Model Layers.

Deep learning algorithms are a subset of the machine learning algorithms, which aim at discovering multiple levels of distributed representations. Recently, numerous deep learning algorithms have been proposed to solve traditional artificial intelligence problems. This work aims to create a state-of-the-art deep learning model with computer vision at its base by highlighting the contributions and challenges from recent research papers. It first goes over the recent studies on the deep learning topics and the discoveries of other brilliant individuals in this field and highlights their successes and how that has contributed to the creation of our model. The system requirements are elaborated to help understand the intensity of work the system has to handle and what minimum level of computational power is required to create these deep learning models, as we know the models are quite computationally power heavy and need a lot of resources and time to work and create these models. Then we see the overview of the system, analysing it as well as its designs using pictorial representations to make understanding of the topic much easier. Finally, we summarize the discussion with the future plans for this deep learning model and how it will be upgraded for obtaining greater results that far surpass the results we have obtained from this project now.

Volume 7 Issue 4, April-2022

Pages : 21 - 26