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.IV20231 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.IV20226 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…