Image Classification
Keras
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@@ -10,7 +10,7 @@ library_name: keras
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  This project provides a ResNet50 pre-trained model for classifying images as either 'real art' or 'fake art'.
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  ResNet50 is a deep convolutional neural network with 50 layers, known for its "residual connections" that help mitigate the vanishing gradient problem.
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  It allows training of very deep networks by adding shortcut connections that skip one or more layers, making it highly effective for image classification tasks.
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- Our goal is to accurately classify the source of the image with at least 85% accuracy and achieve at least 80% in the Recall test.
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  ***Installation instructions***
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  This project provides a ResNet50 pre-trained model for classifying images as either 'real art' or 'fake art'.
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  ResNet50 is a deep convolutional neural network with 50 layers, known for its "residual connections" that help mitigate the vanishing gradient problem.
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  It allows training of very deep networks by adding shortcut connections that skip one or more layers, making it highly effective for image classification tasks.
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+ Our goal is to accurately classify the source of the image with at least 85% accuracy and achieve at least 80% in the recall test.
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  ***Installation instructions***
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