DataScienceProject
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Resnet

Image Classification

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benjaminStreltzin commited on Sep 22, 2024

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@@ -10,7 +10,7 @@ library_name: keras
 This project provides a ResNet50 pre-trained model for classifying images as either 'real art' or 'fake art'.
 ResNet50 is a deep convolutional neural network with 50 layers, known for its "residual connections" that help mitigate the vanishing gradient problem.
 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.
-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.
 ***Installation instructions***

 This project provides a ResNet50 pre-trained model for classifying images as either 'real art' or 'fake art'.
 ResNet50 is a deep convolutional neural network with 50 layers, known for its "residual connections" that help mitigate the vanishing gradient problem.
 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.
+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.
 ***Installation instructions***