Applications of Smartphone-Based Sensors in Agriculture: A Systematic Review of Research. - Suporn Pongnumkul; Pimwadee Chaovalit; Navaporn Surasvadi (J. Sensors, 2015)

A machine learning approach to estimate median income levels of sub-districts in Thailand using satellite and geospatial data. - Ugyen Jigten Dorji; Anon Plangprasopchok; Navaporn Surasvadi; Chaiyaphum Siripanpornchana (GeoAI@SIGSPATIAL, 2019)

Exploring Night Light as Proxy for Poverty and Income Inequality Approximation in Thailand. - Ugyen Jigten Dorji; Chaiyaphum Siripanpornchana; Navaporn Surasvadi; Anon Plangprasopchok; Suttipong Thajchayapong (TENCON, 2019)

A nonparametric framework for inferring orders of categorical data from category-real ordered pairs. - Chainarong Amornbunchornvej; Navaporn Surasvadi; Anon Plangprasopchok; Suttipong Thajchayapong (CoRR, 2019)

Recognizing Traffic Black Spots From Street View Images Using Environment-Aware Image Processing and Neural Network. - Teerapaun Tanprasert; Chaiyaphum Siripanpornchana; Navaporn Surasvadi; Suttipong Thajchayapong (IEEE Access, 2020)

Identifying Linear Models in Multi-Resolution Population Data Using Minimum Description Length Principle to Predict Household Income. - Chainarong Amornbunchornvej; Navaporn Surasvadi; Anon Plangprasopchok; Suttipong Thajchayapong (ACM Trans. Knowl. Discov. Data, 2021)

Framework for inferring empirical causal graphs from binary data to support multidimensional poverty analysis. - Chainarong Amornbunchornvej; Navaporn Surasvadi; Anon Plangprasopchok; Suttipong Thajchayapong (CoRR, 2022)