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CORC

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Classification of Severe and Critical Covid-19 Using Deep Learning and Radiomics 期刊论文
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2020, 卷号: 24, 期号: 12, 页码: 3585-3594
作者:  Li, Cong;  Dong, Di;  Li, Liang;  Gong, Wei;  Li, Xiaohu
收藏  |  浏览/下载：77/0  |  提交时间：2021/03/02
Interval Type-2 Fuzzy Neural Networks for Chaotic Time Series Prediction: A Concise Overview 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2019, 卷号: 49, 页码: 2720-2731
作者:  Han, Min;  Zhong, Kai;  Qiu, Tie;  Han, Bing
收藏  |  浏览/下载：13/0  |  提交时间：2019/12/02
A Review of Computational Intelligence for StarCraft AI 会议论文
Bangalore, India, 18-21 Nov. 2018
作者:  Tang, Zhentao;  Shao, Kun;  Zhu, Yuanheng;  Li, Dong;  Zhao, Dongbin
收藏  |  浏览/下载：38/0  |  提交时间：2019/04/25
DianNao Family: Energy-Efficient Hardware Accelerators for Machine Learning 期刊论文
COMMUNICATIONS OF THE ACM, 2016, 卷号: 59, 期号: 11, 页码: 105-112
作者:  Chen, Yunji;  Chen, Tianshi;  Xu, Zhiwei;  Sun, Ninghui;  Temam, Olivier
收藏  |  浏览/下载：26/0  |  提交时间：2019/12/13
Practical Iterative Optimization for the Data Center 期刊论文
ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION, 2015, 卷号: 12, 期号: 2, 页码: 26
作者:  Fang, Shuangde;  Xu, Wenwen;  Chen, Yang;  Eeckhout, Lieven;  Temam, Olivier
收藏  |  浏览/下载：14/0  |  提交时间：2019/12/13
PuDianNao: A Polyvalent Machine Learning Accelerator 期刊论文
ACM SIGPLAN NOTICES, 2015, 卷号: 50, 期号: 4, 页码: 369-381
作者:  Liu, Daofu;  Chen, Tianshi;  Liu, Shaoli;  Zhou, Jinhong;  Zhou, Shengyuan
收藏  |  浏览/下载：41/0  |  提交时间：2019/12/13
Computational Intelligence in Urban Traffic Signal Control: A Survey 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS, 2012, 卷号: 42, 期号: 4, 页码: 485-494
作者:  Zhao, Dongbin;  Dai, Yujie;  Zhang, Zhen
收藏  |  浏览/下载：30/0  |  提交时间：2015/08/12
Neural network based online traffic signal controller design with reinforcement training (EI CONFERENCE) 会议论文
14th IEEE International Intelligent Transportation Systems Conference, ITSC 2011, October 5, 2011 - October 7, 2011, Washington, DC, United states
Dai Y.; Hu J.; Zhao D.; Zhu F.
收藏  |  浏览/下载：23/0  |  提交时间：2013/03/25
Traffic congestion leads to problems like delays  decreasing flow rate  and higher fuel consumption. Consequently  keeping traffic moving as efficiently as possible is not only important to economy but also important to environment. Traffic system is a large complex nonlinear stochastic system. Traditional mathematical methods have some limitations when they are applied in traffic control. Thus  computational intelligence (CI) technologies gain more and more attentions. Neural Networks (NNs) is a well developed CI technology with lots of promising applications in traffic signal control (TSC). In this paper  a neural network (NN) based signal controller is designed to control the traffic lights in an urban traffic road network. Scenarios of simulation are conducted under a microscopic traffic simulation software. Several criterions are collected. Results demonstrate that through online reinforcement training the controllers obtain better control effects than the widely used pre-time and actuated methods under various traffic conditions. 2011 IEEE.  
Multi-instance learning based on gaussian process for detecting regions of interest 会议论文
5th IASTED International Conference on Computational Intelligence, CI 2010, Maui, HI, 2010-08-23
作者:  He J.;  Gu H.;  Wang Z.
收藏  |  浏览/下载：6/0  |  提交时间：2019/12/24
An United Extended Rough Set Model Based on Developed Set Pair Analysis Method 期刊论文
ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, PROCEEDINGS, 2009, 卷号: Vol.5855, 页码: 9-17
作者:  Wang, LZ;  Xu, Y [ 1 ] Edited by:Deng, H;  By:Ji, X [ 1 ];  Li, LS [ 1 ];  Wang, FL
收藏  |  浏览/下载：4/0  |  提交时间：2019/04/24
Set  pair  analysis  Otherness  Rough  set  United  set  pair  tolerance  relation  

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