The project involved training a model to recognize and classify images into specified categories. Various CNN architectures were utilized, including AlexNet, VGG16, InceptionV3, and ResNet. The model achieved over 97% accuracy with ResNet. Additionally, a responsive web application was developed using HTML, CSS, and JavaScript, and it was deployed on the Heroku web server.
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suhas004/Image-Classification-Using-CNN
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