5 papers
I Detect What I Don't Know: Incremental Anomaly Learning with Stochastic Weight Averaging-Gaussian for Oracle-Free Medical Imaging
Nand Kumar Yadav, Rodrigue Rizk, William CW Chen +1
Unknown anomaly detection in medical imaging remains a fundamental challenge due to the scarcity of labeled anomalies and the high cost of expert supervision. We introduce an unsup…
Toward Carbon-Neutral Human AI: Rethinking Data, Computation, and Learning Paradigms for Sustainable Intelligence
KC Santosh, Rodrigue Rizk, Longwei Wang
The rapid advancement of Artificial Intelligence (AI) has led to unprecedented computational demands, raising significant environmental and ethical concerns. This paper critiques t…
CoSwin: Convolution Enhanced Hierarchical Shifted Window Attention For Small-Scale Vision
Puskal Khadka, Rodrigue Rizk, Longwei Wang +1
Vision Transformers (ViTs) have achieved impressive results in computer vision by leveraging self-attention to model long-range dependencies. However, their emphasis on global cont…
Bi-cephalic self-attended model to classify Parkinson's disease patients with freezing of gait
Shomoita Jahid Mitin, Rodrigue Rizk, Maximilian Scherer +4
Parkinson's Disease (PD) often results in motor and cognitive impairments, including gait dysfunction, particularly in patients with freezing of gait (FOG). Current detection metho…
LakotaBERT: A Transformer-based Model for Low Resource Lakota Language
Kanishka Parankusham, Rodrigue Rizk, KC Santosh
Lakota, a critically endangered language of the Sioux people in North America, faces significant challenges due to declining fluency among younger generations. This paper introduce…