2 papers
eess.IV2026
A Controlled Evaluation of Quantum Correlation Refinement for Few-Shot Semantic Segmentation: Resource Cost and IBM Quantum Hardware Validation
Hina Shakir, Muhammad Irfan Memon, Asia Samreen +4
PQCs are increasingly proposed as trainable components in classical ML pipelines, but rarely characterized alongside a controlled measurement of task-level benefit. We report such…
cs.CV2026
Radiomic Feature Selection Using Gradient Loss of Deep Neural Network for Lung Cancer Stage Detection
Hina Shakir, Mohammad Mohatram, Javeed Hussain +2
Radiomics enables extraction of quantitative imaging biomarkers from medical images and has become an important tool for computer-aided cancer diagnosis. However, radiomics dataset…