Authors : Amruth N Murthy; Kavana N Murthy; Dr. Shivandappa; Dr. Narendra Kumar S

Volume/Issue : Volume 9 - 2024, Issue 8 - August

Google Scholar : https://tinyurl.com/kbb3sh4c

Scribd : https://tinyurl.com/4x2cvrrj

DOI : https://doi.org/10.38124/ijisrt/IJISRT24AUG974

Abstract : Butterfly species identification through image classification is now a major use of computer vision, utilizing supervised learning methods to classify different types of butterflies based on images. This article gives a detailed overview of the latest progress in classifying butterfly images through supervised learning techniques on Google Colab, a widely-used cloud-based platform for machine learning projects. The review starts by discussing the significance of precise butterfly categorization for biodiversity research and conservation endeavors. It then goes into specifics about different methods used in supervised learning for this purpose, such as convolutional neural networks (CNNs), support vector machines (SVMs), and k-nearest neighbors (k-NN). The review discusses the pros and cons of using these methods on butterfly image data, emphasizing on accuracy, efficiency, and generalization. Special focus is placed on the preprocessing procedures necessary to improve image quality and extract features, including image augmentation, normalization, and feature scaling. The article also investigates various butterfly image datasets that are accessible to the public, analyzing how they are used for training and assessing classification models. Google Colab is highlighted as a potent instrument for creating and testing these models because of its convenience, user-friendliness, and compatibility with leading machine learning libraries such as TensorFlow and PyTorch. Furthermore, the article examines recent research and initiatives that have effectively utilized butterfly image categorization with Colab, demonstrating ideal methods and insight gained. Image Preprocessing, Feature Extraction, Machine Learning Libraries, TensorFlow, PyTorch, Image Augmentation, Publicly Available Datasets.

Keywords : Butterfly Image Classification, Supervised Learning, Google Colab, Convolutional Neural Networks (Cnns), Support Vector Machines (Svms), K-Nearest Neighbors (K-NN),

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