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@article{188539,
        author = {Sindhu M V and Thrupthi H R and Varsha U Nagesh and Sushmitha H K and Shashidhara H V},
        title = {Deep Learning-Based Detection of Fake Images, Videos and News},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {2124-2133},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=188539},
        abstract = {This research presents an integrated web platform for identifying synthetic media and textual misinformation. The system utilizes a multi-model approach, combining a transfer-learned Xception network for image analysis, a hybrid CNN-LSTM architecture for video assessment, and a TF-IDF with Logistic Regression pipeline for news verification. Implemented using Flask and TensorFlow, the framework processes user-uploaded content through specialized detection modules, delivering real-time authenticity assessments with confidence metrics. Experimental results demonstrate 95% efficacy in image-based deepfake recognition and 88% accuracy in video manipulation detection, providing a comprehensive solution for digital content authentication across multiple media formats.},
        keywords = {Media Forensics, Deepfake Detection, Multimodal Verification, Neural Networks, Content Authentication, Web-Based System},
        month = {December},
        }