2 papers
cs.CV2026
TRIUNE-Net: Harmonizing Scale, Shape, and Efficiency in Pancreatic Tumor Segmentation
Amir Hossein Saleknia, Alireza Kheyrkhah, Sanaz Karimijafarbigloo +5
Pancreatic tumor segmentation in 3D CT volumes is challenged by extreme scale variability across both the pancreas and tumor, and highly irregular tumor morphology. While recent ad…
cs.CV2026
What Are We Really Measuring? Rethinking Dataset Bias in Web-Scale Natural Image Collections via Unsupervised Semantic Clustering
Amir Hossein Saleknia, Mohammad Sabokrou
In computer vision, a prevailing method for quantifying dataset bias is to train a model to distinguish between datasets. High classification accuracy is then interpreted as eviden…