Instructions to use DataScienceProject/CNN_And_ELA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use DataScienceProject/CNN_And_ELA with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://DataScienceProject/CNN_And_ELA") - Notebooks
- Google Colab
- Kaggle
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README.md
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# Model Card for Model ID
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This model is designed for classifying images as either 'real' or 'fake-
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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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# Model Card for Model ID
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This model is designed for classifying images as either 'real' or 'fake-AI generated' using a Convolutional Neural Network (CNN) combined with Error Level Analysis (ELA).
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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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