Performing Image Classification for 10 Different Monkey Species using CNN
Emmanuel Maduwuba, Dharanikota Rajendra Kamal and Kamaljeet Singh Mann. Western University of Ontario
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the main aim of this project is to achieve fine grain image classification by applying a suitable machine learning architecture to the set of images present in the dataset. The chosen dataset is taken as a part of the Kaggle competition and is selected from Wikipedia's monkey cladogram and this dataset contains 10 different species of monkeys which are to be classified with the help of a machine learning architecture augmented by Image processing. After having brief exposure and using several architectures to classify this dataset, the Convolutional Neural network was found to be the best fit.