53 citations · 85 across the 8 of their papers we have counts for
8 papers
All Grains, One Scheme (AGOS): Learning Multi-grain Instance Representation for Aerial Scene Classification
Qi Bi, Beichen Zhou, Kun Qin +2
Aerial scene classification remains challenging as: 1) the size of key objects in determining the scene scheme varies greatly; 2) many objects irrelevant to the scene scheme are of…
AI-based Medical e-Diagnosis for Fast and Automatic Ventricular Volume Measurement in the Patients with Normal Pressure Hydrocephalus
Xi Zhou, Qinghao Ye, Xiaolin Yang +5
Based on CT and MRI images acquired from normal pressure hydrocephalus (NPH) patients, using machine learning methods, we aim to establish a multi-modal and high-performance automa…
Exploring Global Diversity and Local Context for Video Summarization
Yingchao Pan, Ouhan Huang, Qinghao Ye +4
Video summarization aims to automatically generate a diverse and concise summary which is useful in large-scale video processing. Most of the methods tend to adopt self-attention m…
Robust Weakly Supervised Learning for COVID-19 Recognition Using Multi-Center CT Images
Qinghao Ye, Yuan Gao, Weiping Ding +8
The world is currently experiencing an ongoing pandemic of an infectious disease named coronavirus disease 2019 (i.e., COVID-19), which is caused by the severe acute respiratory sy…
Explainable AI For COVID-19 CT Classifiers: An Initial Comparison Study
Qinghao Ye, Jun Xia, Guang Yang
Artificial Intelligence (AI) has made leapfrogs in development across all the industrial sectors especially when deep learning has been introduced. Deep learning helps to learn the…
Unbox the Black-box for the Medical Explainable AI via Multi-modal and Multi-centre Data Fusion: A Mini-Review, Two Showcases and Beyond
Guang Yang, Qinghao Ye, Jun Xia
Explainable Artificial Intelligence (XAI) is an emerging research topic of machine learning aimed at unboxing how AI systems' black-box choices are made. This research field inspec…
Exploring global diverse attention via pairwise temporal relation for video summarization
Ping Li, Qinghao Ye, Luming Zhang +3
Video summarization is an effective way to facilitate video searching and browsing. Most of existing systems employ encoder-decoder based recurrent neural networks, which fail to e…
Application of Time Series Analysis to Traffic Accidents in Los Angeles
Qinghao Ye, Kaiyuan Hu, Yizhe Wang
With the improvements of Los Angeles in many aspects, people in mounting numbers tend to live or travel to the city. The primary objective of this paper is to apply a set of method…