Evaluating Deep Learning and Traditional Approaches Used in Source Camera Identification
cs.CV
Submitted: 2025-11-24
Updated: 2026-10-19
Comments: 6 pages, 5 figures, 1 table. Version submitted to SIDe'26 (International Conference on Secure and Intelligent Digital Ecosystems) (Astana, Oct 2026) before peer review. The paper was accepted and will appear in the Springer STEAM-H series; the accepted version uses repeated cross-validation and reports updated results
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Related papers
- Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
- AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
- Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
- MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
- TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
- A Survey on Efficient Vision-Language-Action Models