An AI image detection tool was built to differentiate between real and AI-generated images using a dataset, logical structuring, and a convolutional neural network. The project involved detailed steps including database structuring, image labeling, model selection, and portability of the trained model. Despite facing technical challenges, the prototype reached a high accuracy level, demonstrating the possibilities of implementing AI tools in everyday settings. The final product can be shared publicly and integrated into various applications across platforms.
The model was trained on two datasets: one of real images and one of AI-generated ones. Each image was resized, normalised, and fed into a convolutional neural network. After many training rounds, the model reached a reliable accuracy.
The idea behind the tool is simple. You give it an image. It tells you whether it's real or AI-generated.
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