activity
20192025
most citedA Deep Learning Approach to Radar-based QPE

29 citations · 56 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Learning Representations of Satellite Images with Evaluations on Synoptic Weather Events

Ting-Shuo Yo, Shih-Hao Su, Chien-Ming Wu +4

This study applied representation learning algorithms to satellite images and evaluated the learned latent spaces with classifications of various weather events. The algorithms inv…

physics.ao-ph2024★ 29 cited

A Deep Learning Approach to Radar-based QPE

Ting-Shuo Yo, Shih-Hao Su, Jung-Lien Chu +2

In this study, we propose a volume-to-point framework for quantitative precipitation estimation (QPE) based on the Quantitative Precipitation Estimation and Segregation Using Multi…

physics.ao-ph2019★ 20 cited

Identification of synoptic weather types over Taiwan area with multiple classifiers

Shih-Hao Su, Jung-Lien Chu, Ting-Shuo Yo +1

In this study, a novel machine learning approach was used to classify three types of synoptic weather events in Taiwan area from 2001 to 2010. We used reanalysis data with three ma…

cs.CL2019★ 3 cited

A realistic and robust model for Chinese word segmentation

Chu-Ren Huang, Ting-Shuo Yo, Petr Simon +1

A realistic Chinese word segmentation tool must adapt to textual variations with minimal training input and yet robust enough to yield reliable segmentation result for all variants…

cs.NE2019★ 4 cited

A comparison of evaluation methods in coevolution

Ting-Shuo Yo, Edwin de Jong

In this research, we compare four different evaluation methods in coevolution on the Majority Function problem. The size of the problem is selected such that evaluation against all…