Prabhjot Singh

Future Generation Computer Systems

A multi-branch hierarchical framework for counterfeit image manipulation localization using noise and frequency features

Experimental evaluations on benchmark forensic datasets demonstrate that the proposed framework achieves competitive detection performance and robustness across most datasets, attaining an AUC of up to 0.998 on NIST16, while highlighting specific failure modes on challenging cases such as COVERAGE.

How Much Reconstruction Does Quantum Machine Learning Need? Late Fusion of Independently Trained Quantum Subcircuits

Late fusion is an efficient, noise-robust, self-characterizing alternative to reconstruction for circuit-cutting QML and claims advantage over classical machine learning - consistent with recent benchmarking, quantum offers no accuracy edge on these datasets.