84 citations · 129 across the 9 of their papers we have counts for
9 papers
Semantic Compositional Learning for Low-shot Scene Graph Generation
Tao He, Lianli Gao, Jingkuan Song +2
Scene graphs provide valuable information to many downstream tasks. Many scene graph generation (SGG) models solely use the limited annotated relation triples for training, leading…
Exploiting Scene Graphs for Human-Object Interaction Detection
Tao He, Lianli Gao, Jingkuan Song +1
Human-Object Interaction (HOI) detection is a fundamental visual task aiming at localizing and recognizing interactions between humans and objects. Existing works focus on the visu…
A Computer-Aided Diagnosis System for Breast Pathology: A Deep Learning Approach with Model Interpretability from Pathological Perspective
Wei-Wen Hsu, Yongfang Wu, Chang Hao +6
Objective: We develop a computer-aided diagnosis (CAD) system using deep learning approaches for lesion detection and classification on whole-slide images (WSIs) with breast cancer…
Learning from the Scene and Borrowing from the Rich: Tackling the Long Tail in Scene Graph Generation
Tao He, Lianli Gao, Jingkuan Song +2
Despite the huge progress in scene graph generation in recent years, its long-tail distribution in object relationships remains a challenging and pestering issue. Existing methods…
One Network for Multi-Domains: Domain Adaptive Hashing with Intersectant Generative Adversarial Network
Tao He, Yuan-Fang Li, Lianli Gao +2
With the recent explosive increase of digital data, image recognition and retrieval become a critical practical application. Hashing is an effective solution to this problem, due t…
Understanding the Mechanism of Deep Learning Framework for Lesion Detection in Pathological Images with Breast Cancer
Wei-Wen Hsu, Chung-Hao Chen, Chang Hoa +7
The computer-aided detection (CADe) systems are developed to assist pathologists in slide assessment, increasing diagnosis efficiency and reducing missing inspections. Many studies…