activity
20202022
most citedClassification of Abnormal Hand Movement for Aiding in Autism Detection: Machine Learning Study

55 citations · 76 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2022★ 1 cited

An Exploration of Active Learning for Affective Digital Phenotyping

Peter Washington, Cezmi Mutlu, Aaron Kline +9

Some of the most severe bottlenecks preventing widespread development of machine learning models for human behavior include a dearth of labeled training data and difficulty of acqu…

cs.CV2022★ 6 cited

Challenges and Opportunities for Machine Learning Classification of Behavior and Mental State from Images

Peter Washington, Cezmi Onur Mutlu, Aaron Kline +7

Computer Vision (CV) classifiers which distinguish and detect nonverbal social human behavior and mental state can aid digital diagnostics and therapeutics for psychiatry and the b…

cs.CV2021★ 55 cited

Classification of Abnormal Hand Movement for Aiding in Autism Detection: Machine Learning Study

Anish Lakkapragada, Aaron Kline, Onur Cezmi Mutlu +5

A formal autism diagnosis can be an inefficient and lengthy process. Families may wait months or longer before receiving a diagnosis for their child despite evidence that earlier i…

cs.CV2021

Activity Recognition with Moving Cameras and Few Training Examples: Applications for Detection of Autism-Related Headbanging

Peter Washington, Aaron Kline, Onur Cezmi Mutlu +6

Activity recognition computer vision algorithms can be used to detect the presence of autism-related behaviors, including what are termed "restricted and repetitive behaviors", or…

cs.CV2021

Training Affective Computer Vision Models by Crowdsourcing Soft-Target Labels

Peter Washington, Onur Cezmi Mutlu, Emilie Leblanc +8

Emotion classifiers traditionally predict discrete emotions. However, emotion expressions are often subjective, thus requiring a method to handle subjective labels. We explore the…

cs.CV2020★ 14 cited

Improved Digital Therapy for Developmental Pediatrics Using Domain-Specific Artificial Intelligence: Machine Learning Study

Peter Washington, Haik Kalantarian, John Kent +16

Background: Automated emotion classification could aid those who struggle to recognize emotions, including children with developmental behavioral conditions such as autism. However…