NEURAL MIRROR: AI-POWERED DEEPFAKE DETECTION - Bhosale Om Santosh; Dolle Akhilish Banasiddha; Kadganchi Manas Nagesh; Gambhire Kshitij Vinod; Mhamane Shivraj Vishwanath; Nagesh Anand Goden (JournalNX - A Multidisciplinary Peer Reviewed Journal, 2025)
In an era where artificial intelligence can replicate human likeness with alarming precision, the ability to distinguish authentic images from synthetically generated ones has become critically important. This paper introduces Neural Mirror, an AI-powered deepfake detection system designed to identify manipulated or AI-generated facial images with high accuracy. Leveraging a custom-trained deep learning model, Neural Mirror focuses on detecting subtle visual artifacts and inconsistencies commonly present in synthetic media. The system analyses facial textures, lighting mismatches, and structural irregularities that often escape the human eye, yet are detectable through deep neural pattern recognition. A user-friendly frontend powered by modern web technologies, including React, TypeScript, and Tailwind CSS, ensures real-time interaction and instant feedback. Neural Mirror aims to serve as a proactive tool in the fight against digital misinformation, enhancing trust in visual media and supporting ethical AI deployment.