Enhanced Toy Image Classification using Convolutional Neural Networks and Deep Learning

This paper presents an innovative approach towards image classification using deep learning techniques, specifically focusing on the application of convolutional neural networks (CNNs). The primary objective is to develop a system capable of accurately identifying and classifying images of different toy categories. The proposed system leverages TensorFlow and Keras libraries for model development and Streamlit for building an interactive user interface. The methodology involves loading a pre-trained CNN model trained on a dataset containing images of toy categories. Upon user input of an image, the system processes the image through the pre-trained model, extracting features and making predictions regarding its classification.