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This paper proposes a novel framework for deepfake image recognition for athletic celebrities using locality sensitive hashing (LSH). LSH, an efficient technique for high\u2010dimensional nearest neighbor searches, is employed to detect and differentiate deepfake images from authentic media. By extracting high\u2010dimensional features from images and videos using convolutional neural networks (CNNs), LSH is applied to hash similar content into clusters for quick and accurate deepfake detection. The proposed method is tested on real\u2010world dataset, showing promising results in terms of accuracy and computational efficiency. 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