3 citations · 4 across the 6 of their papers we have counts for
6 papers
Fine-tuning a multimodal large language model for clinician-grade autism behavioral scoring from short home videos
Mohammadmahdi Honarmand, Parnian Azizian, Aaron Kline +9
Autism spectrum disorder (ASD) affects 1 in 31 US children, yet median age at diagnosis exceeds four years. Artificial intelligence pipelines that provide quantified diagnosis usin…
FIESTA: Fisher Information-based Efficient Selective Test-time Adaptation
Mohammadmahdi Honarmand, Onur Cezmi Mutlu, Parnian Azizian +2
Robust facial expression recognition in unconstrained, "in-the-wild" environments remains challenging due to significant domain shifts between training and testing distributions. T…
VidLPRO: A eo-anguage re-training Framework for botic and Laparoscopic Surgery
Mohammadmahdi Honarmand, Muhammad Abdullah Jamal, Omid Mohareri
We introduce VidLPRO, a novel video-language (VL) pre-training framework designed specifically for robotic and laparoscopic surgery. While existing surgical VL models primarily rel…
Ensemble Modeling of Multiple Physical Indicators to Dynamically Phenotype Autism Spectrum Disorder
Marie Huynh, Aaron Kline, Saimourya Surabhi +6
Early detection of autism, a neurodevelopmental disorder marked by social communication challenges, is crucial for timely intervention. Recent advancements have utilized naturalist…
TempT: Temporal consistency for Test-time adaptation
Onur Cezmi Mutlu, Mohammadmahdi Honarmand, Saimourya Surabhi +1
We introduce Temporal consistency for Test-time adaptation (TempT) a novel method for test-time adaptation on videos through the use of temporal coherence of predictions across seq…
Computer Vision Estimation of Emotion Reaction Intensity in the Wild
Yang Qian, Ali Kargarandehkordi, Onur Cezmi Mutlu +4
Emotions play an essential role in human communication. Developing computer vision models for automatic recognition of emotion expression can aid in a variety of domains, including…