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@article{172590,
        author = {JAYANTH N and DR. J V GORABAL and MANOJ KUMAR and MEGHA H M and MANOJ KUMAR C M},
        title = {Image Forensics},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {9},
        pages = {280-282},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=172590},
        abstract = {Deepfake technology has advanced significantly, leading to concerns about digital media integrity. This paper presents a deep learning-based approach for deepfake detection using convolutional neural networks (CNN) and image preprocessing techniques such as Gaussian Blur, Histogram Equalization, Sobel Filtering, and Edge Detection. The model is trained on a dataset of real and fake images, achieving high accuracy in classification. This study highlights the importance of image preprocessing in enhancing model performance and provides insights into the effectiveness of different preprocessing techniques in deepfake detection.},
        keywords = {Deepfake detection, image preprocessing, convolutional neural networks, machine learning, digital forensics.},
        month = {January},
        }