Artificial Intelligence & Machine Learning

A Deep Learning-Based Compression-Robust Framework for Deepfake Detection with Cross-Dataset Generalization and Explainability

A robust deepfake detection framework focused on compression resilience, cross-dataset generalization, and explainability.

A Deep Learning-Based Compression-Robust Framework for Deepfake Detection with Cross-Dataset Generalization and Explainability

Project Information

Category: Artificial Intelligence & Machine Learning

Created: August 2026

Project Description

Researcher: Sagar | PSIT, Kanpur Developing a robust deepfake detection framework with emphasis on compression resilience, cross-dataset generalization, and explainable model predictions. Status: Ongoing

Related Projects

Claim-Level Evidence Verification for Detecting Unsupported Statements in RAG Responses
Claim-Level Evidence Verification for Detecting Unsupported Statements in RAG Responses

A claim-level verification framework to detect unsupported statements in RAG-generated responses.

View Project
VBRL Assistant