Author: Youngjun Cho

Automatic Recognition of Psychological States (eg. Mental Stress)

With sensing technology becoming pervasive in our everyday life, the ability to monitor human psychological states has become important in human computer interaction. Amongst such states, high level mental stress or mental workload is a common problem affecting mental, physical

Deep Thermal Imaging Toolkit @CHI2018

Full source codes are available at https://github.com/deepneuroscience/DeepThermalImaging 1. Requirement Matlab (version>2012) MatConvNet (https://github.com/vlfeat/matconvnet): Deep CNN Framework for Matlab users. 2. Quick Summary DEEP THERMAL IMAGING – Main Libraries Void deep_thermal_imaging_training_and_testing(kfold, numberofclass, filename, directory, isoutdoor) Trains and Tests on the given

Biomedical Optics Express Journal Paper: Supplementary Materials

Robust Tracking of Respiratory Rate

An example clip to show the performance of the proposed method (from Dataset1 – controlled respiration in environments with non-constant temperature) An example clip to show the performance of the proposed method (from Dataset2 – unconstrained respiration with natural motion

Matlab source codes: Stress Induction Tasks for “DeepBreath” @ACII2017

Source code for “DeepBreath Project” Description: We propose DeepBreath, a deep learning model which automatically recognises people’s psychological stress level (mental overload) from their breathing patterns. Using a low cost thermal camera, we track a person’s breathing patterns as temperature

Computer Science Conference Ranking 2017/2018 – Prestigious Top 4 by “Research Area”

Youngjun Cho - Computer Science Conference Ranking

(Source: Google Scholar Metrics) # Human Computer Interaction   Conference H5-index Computer Human Interaction (CHI) 83 ACM Conference on Computer-Supported Cooperative Work & Social Computing (CSCW) 49 ACM Symposium on User Interface Software and Technology (UIST) 44 ACM Conference on Pervasive

Top