Deep Neural Network + Hidden Markov Model
Project Description
This is a Cognitive Science project where we use computational models to understand human cognition. We will use our proposed Deep Neural Network + Hidden Markov Model (DNN+HMM; https://www.nature.com/articles/s41539-022-00139-6) to model face or object recognition, aiming to account for face or object recognition effects and deficits observed in human data, including those observed in autistic individuals. This is suitable for students with computational/engineering backgrounds with an interest on human cognition.
Supervisor
HSIAO, Janet Hui-wen
Quota
1
Course type
UROP1100
Applicant's Roles
Building on our team's previous work, the applicant will continue developing the model for accounting for various face or object recognition effects, and assist in relevant data analysis and report preparation.
Applicant's Learning Objectives
- To learn to perform modelling with DNN+HMM
- To learn to account for face or object recognition effects or deficits in human data, and perform relevant data analysis
- To learn to present results and prepare reports.
- To learn to account for face or object recognition effects or deficits in human data, and perform relevant data analysis
- To learn to present results and prepare reports.
Complexity of the project
Challenging