benjaminStreltzin
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Update README.md
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README.md
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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
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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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