Multi-feature Forgery Detection Deep-Learning based Framework
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Updated
Feb 6, 2024 - JavaScript
Multi-feature Forgery Detection Deep-Learning based Framework
Bag of visual words AI model made with Scikit-learn and OpenCV
[ICAPR 2017] Image Hash Minimization for Tamper Detection
Bachelor's Thesis - application for detecting digital image forgeries. Praca Inzynierska - aplikacja do wykrywania falszerstw w obrazach cyfrowych
TensorFlow/Keras examples and notes.
A Rust implementation of ZERO: a JPEG grid detector applied to forgery detection in digital images.
Iterative Copy-Move Forgery Detection based on a new Interest Point Detector
An algorithm that is completely robust to Intensity/ Brightness varied copy move forgery is proposed in this algorithm.
Forgegy Image Detection Using Error level Analysis and Deep Learning
Authenticating Bob Ross Paintings using Convolutional Neural Networks
Implementation of the famous Camera Noise Fingerprint "NoisePrint" in Pytorch
Implementing Copy Move Forgery Detection using DCT or SVD transformations. Also, a clear explanation is provided in the READme section
IMDetector is a Python module for image manipulation detection.
Employing Error Level Analysis (ELA) and Edge Detection techniques, this project aims to identify potential image forgery by analyzing discrepancies in error levels and abrupt intensity changes within images.
The assignments and projects on Digital Image Processing
auto-encoder-based forgery detection tool for mammogram images
A deep convolutional neural network for the detection as well as localization of the area of manipulation in forged images, bearing forgeries of simple as well as complex nature. Further along, the trained model is interfaced with a web application for users to interact with the model in a simple and effective manner, and finally, we also develo…
Official implementation of the article "Unsupervised JPEG Domain Adaptation For Practical Digital Forensics"
This is the one of solution implemented for image forgery localization using deep learning techniques and architectures such as UNET, VGG
image fraud detection(copy-move forgery)
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