activity
20152022
most citedOne-Shot Object Detection with Co-Attention and Co-Excitation

116 citations · 290 across the 10 of their papers we have counts for

collaborators

13 papers

cs.CV202036 cited

Learning Gaussian Instance Segmentation in Point Clouds

Shih-Hung Liu, Shang-Yi Yu, Shao-Chi Wu +2

This paper presents a novel method for instance segmentation of 3D point clouds. The proposed method is called Gaussian Instance Center Network (GICN), which can approximate the di…

eess.IV20202 cited

Self-similarity Student for Partial Label Histopathology Image Segmentation

Hsien-Tzu Cheng, Chun-Fu Yeh, Po-Chen Kuo +6

Delineation of cancerous regions in gigapixel whole slide images (WSIs) is a crucial diagnostic procedure in digital pathology. This process is time-consuming because of the large…

cs.SI20203 cited

Social Distancing 2.0 with Privacy-Preserving Contact Tracing to Avoid a Second Wave of COVID-19

Yu-Chen Ho, Yi-Hsuan Chen, Shen-Hua Hung +7

How to avoid a second wave of COVID-19 after reopening the economy is a pressing question. The extremely high basic reproductive number (5.7 to 6.4, shown in new studies) of…

eess.IV202036 cited

A Cascaded Learning Strategy for Robust COVID-19 Pneumonia Chest X-Ray Screening

Chun-Fu Yeh, Hsien-Tzu Cheng, Andy Wei +20

We introduce a comprehensive screening platform for the COVID-19 (a.k.a., SARS-CoV-2) pneumonia. The proposed AI-based system works on chest x-ray (CXR) images to predict whether a…

cs.CV2019116 cited

One-Shot Object Detection with Co-Attention and Co-Excitation

Ting-I Hsieh, Yi-Chen Lo, Hwann-Tzong Chen +1

This paper aims to tackle the challenging problem of one-shot object detection. Given a query image patch whose class label is not included in the training data, the goal of the ta…

cs.CV2019

ACE: Adaptive Confusion Energy for Natural World Data Distribution

Yen-Chi Hsu, Cheng-Yao Hong, Wan-Cyuan Fan +3

With the development of deep learning, standard classification problems have achieved good results. However, conventional classification problems are often too idealistic. Most dat…