activity
20222024
most citedSpatiotemporal Feature Learning Based on Two-Step LSTM and Transformer for CT Scans

6 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

cs.MM2024

Revisiting Vision-Language Features Adaptation and Inconsistency for Social Media Popularity Prediction

Chih-Chung Hsu, Chia-Ming Lee, Yu-Fan Lin +3

Social media popularity (SMP) prediction is a complex task involving multi-modal data integration. While pre-trained vision-language models (VLMs) like CLIP have been widely adopte…

eess.IV2024

A Closer Look at Spatial-Slice Features Learning for COVID-19 Detection

Chih-Chung Hsu, Chia-Ming Lee, Yang Fan Chiang +4

Conventional Computed Tomography (CT) imaging recognition faces two significant challenges: (1) There is often considerable variability in the resolution and size of each CT scan,…

eess.IV2024

Simple 2D Convolutional Neural Network-based Approach for COVID-19 Detection

Chih-Chung Hsu, Chia-Ming Lee, Yang Fan Chiang +4

This study explores the use of deep learning techniques for analyzing lung Computed Tomography (CT) images. Classic deep learning approaches face challenges with varying slice coun…

eess.IV2023★ 1 cited

Strong Baseline and Bag of Tricks for COVID-19 Detection of CT Scans

Chih-Chung Hsu, Chih-Yu Jian, Chia-Ming Lee +2

This paper investigates the application of deep learning models for lung Computed Tomography (CT) image analysis. Traditional deep learning frameworks encounter compatibility issue…

eess.IV2022★ 6 cited

Spatiotemporal Feature Learning Based on Two-Step LSTM and Transformer for CT Scans

Chih-Chung Hsu, Chi-Han Tsai, Guan-Lin Chen +2

Computed tomography (CT) imaging could be very practical for diagnosing various diseases. However, the nature of the CT images is even more diverse since the resolution and number…