Comparative analysis of classical ML models (SVM, Random Forest) and CNN architectures (LeNet5, AlexNet, VGG16, ResNet50, InceptionV3, MobileNetV2) for multi-class image classification. Includes training, evaluation, and performance benchmarking across models.
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Comparative analysis of classical ML models (SVM, Random Forest) and CNN architectures (LeNet5, AlexNet, VGG16, ResNet50, InceptionV3, MobileNetV2) for multi-class image classification. Includes training, evaluation, and performance benchmarking across models.
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KrishangJain/MultiModel-ImageClassifier-Project
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Comparative analysis of classical ML models (SVM, Random Forest) and CNN architectures (LeNet5, AlexNet, VGG16, ResNet50, InceptionV3, MobileNetV2) for multi-class image classification. Includes training, evaluation, and performance benchmarking across models.
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