GitHub

Few-Shot Synthetic Image Attribution: Identifying Unseen Generators with Limited Samples

Generative models now forge photorealistic images that defy visual scrutiny, collapsing the boundary between authentic and synthetic. Existing attribution methods operate in a closed-set manner — they ...
IEEE

D2S-RSG-SSD: Dual Double-Sampling with Random Sub-Samples Generation for Self-Supervised Real Image Denoising

Abstract: Recent advances in self-supervised image denoising have highlighted the potential of Blind-Spot Networks (BSNs). However, existing methods suffer from three major limitations: (1) Their ...
IEEE

Dataset Pruning: Optimizing Image Datasets with a Cross-Validation Method

In the field of image recognition, the scale and diversity of datasets are crucial for model training. This study proposes a novel cross-validation dataset pruning method with data balancing (CVDP-DB) ...
The Lancet

Risk-stratified classification of pulmonary nodule malignancy via a machine learning model integrating imaging and cell-free DNA: a model development and validation study ...

aDepartment of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for ...