Year: 2024
Type: article
Abstract: This paper introduces a hybrid architecture combining Long Short-Term Memory (LSTM) networks and an encoderdecoder model for the detection and localization of image and video forgeries. The proposed system leverages resampling features and LSTM cells to identify manipulation patterns such as splicing and retouching in multimedia content. By utilizing a combination of spatial and temporal features, the model achieves high precision in detecting forged regions. Extensive testing on diverse datasets demonstrates the robustness of the proposed method.
Author: Uday Sai Kiran Vangaru
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4403200259