Papers › Performing Image Classification for 10 Different Monkey Species using CNN
Performing Image Classification for 10 Different Monkey Species using CNN
Emmanuel Maduwuba, Dharanikota Rajendra Kamal and Kamaljeet Singh Mann. Western University of Ontario
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.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Fine-Grained Image Classification | 10 Monkey Species | CNN | Accuracy | 95.00 | #4 of 4 | Archive leaderboard | report |
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