1 citations · 1 across the 6 of their papers we have counts for
8 papers
Is invariance all you need for algorithmic fairness? Removing demographic information can create new bias
Aditya Parikh, Eike Petersen, Stella Frank +3
Encoded demographic information in internal model representations is a commonly assumed risk factor for algorithmic bias, with demographic representation invariance often being tou…
False Confidence: Automated Labels Confound Fairness Audits in Cervical Spine Segmentation
Linus Juni, Aasa Feragen, Aditya Parikh
Automated segmentation of cervical-spine MRI is increasingly used in clinical workflows, yet no fairness audit exists for this anatomy. We show that auditing these segmentation tas…
Towards Fairness under Label Bias in Image Segmentation: Impact, Measurement and Mitigation
Aditya Parikh, Stella Frank, Sneha Das +1
Biases in annotation pipelines may introduce label bias: when annotation quality or style varies systematically across demographic subgroups, causing disparities in performance and…
Investigating Label Bias and Representational Sources of Age-Related Disparities in Medical Segmentation
Aditya Parikh, Sneha Das, Aasa Feragen
Algorithmic bias in medical imaging can perpetuate health disparities, yet its causes remain poorly understood in segmentation tasks. While fairness has been extensively studied in…
Who Does Your Algorithm Fail? Investigating Age and Ethnic Bias in the MAMA-MIA Dataset
Aditya Parikh, Sneha Das, Aasa Feragen
Deep learning models aim to improve diagnostic workflows, but fairness evaluation remains underexplored beyond classification, e.g., in image segmentation. Unaddressed segmentation…
Exploring Facial Biomarkers for Detecting Depression through Temporal Analysis of Action Units
Aditya Parikh, Misha Sadeghi, Robert Richer +9
Depression is characterized by persistent sadness and loss of interest, significantly impairing daily functioning and now a widespread mental disorder. Traditional diagnostic metho…
Automatic Image Colourizer
Aditya Parikh
In this project we have designed and described a model which colourize a gray-scale image, with no human intervention. We propose a fully automatic process of colouring and re-colo…
Information Extraction from Unstructured data using Augmented-AI and Computer Vision
Aditya Parikh
Information extraction (IE) from unstructured documents remains a critical challenge in data processing pipelines. Traditional optical character recognition (OCR) methods and conve…