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Title: Image Forgery Detection Using Deep Learning | IEEE 2024-25

📌 Project Overview:
This project presents a Deep Learning-based Image Forgery Detection system to identify manipulated or tampered images. Using Convolutional Neural Networks (CNNs) and advanced AI techniques, the model efficiently detects forged regions in images, making it a crucial tool for digital forensics and media authentication.

🔍 Key Features:
✅ Deep Learning-based image forgery detection
✅ Detection of copy-move, splicing, and retouching forgeries
✅ Dataset preprocessing and feature extraction
✅ High accuracy using CNNs & Transfer Learning
✅ Implementation of latest IEEE 2024-25 research

🎯 Best Suited For:
🔹 B.Tech, M.Tech, MCA, BCA Final Year Projects
🔹 AI, ML, and Deep Learning Enthusiasts
🔹 Students & Researchers in Image Processing & Cybersecurity

📁 Project Deliverables:
✔ Source Code & Dataset
✔ Project Report & Documentation
✔ Research Paper Reference (IEEE 2024-25)
✔ Implementation Guidance

🚀 Why Choose This Project?
With the rise of fake images and digital manipulation, detecting image forgery is essential for cybersecurity, journalism, and digital forensics. This project applies cutting-edge Deep Learning techniques to ensure authenticity and reliability.

📞 Need Help? Contact Us!
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🔖 Tags:
#IEEE2024 #FinalYearProject #DeepLearning #MachineLearning #AI #ImageForgeryDetection #ForgeryDetection #DigitalForensics #ImageProcessing #CNN #TransferLearning #BTechProjects #MTechProjects #MCAProjects #BCAProjects #AIinForensics #CyberSecurity #NeuralNetworks #Python #Colab #DLModels #Research #CollegeProjects #FakeImageDetection