Open Science Research Excellence

ICRLN 2020 : International Conference on Robot Learning and Neurocybernetics

Kuala Lumpur, Malaysia
February 10 - 11, 2020

Conference Code: 20MY02ICRLN

Conference Proceedings

All submitted conference papers will be blind peer reviewed by three competent reviewers. The peer-reviewed conference proceedings are indexed in the Open Science Index, Google Scholar, Semantic Scholar, Zenedo, OpenAIRE, BASE, WorldCAT, Sherpa/RoMEO, and other index databases. Impact Factor Indicators.

Special Journal Issues

ICRLN 2020 has teamed up with the Special Journal Issue on Robot Learning and Neurocybernetics. A number of selected high-impact full text papers will also be considered for the special journal issues. All submitted papers will have the opportunity to be considered for this Special Journal Issue. The paper selection will be carried out during the peer review process as well as at the conference presentation stage. Submitted papers must not be under consideration by any other journal or publication. The final decision for paper selection will be made based on peer review reports by the Guest Editors and the Editor-in-Chief jointly. Selected full-text papers will be published online free of charge.

Conference Sponsor and Exhibitor Opportunities

The Conference offers the opportunity to become a conference sponsor or exhibitor. To participate as a sponsor or exhibitor, please download and complete the Conference Sponsorship Request Form.

Important Dates

Abstracts/Full-Text Paper Submission Deadline   December 30, 2019
Notification of Acceptance/Rejection   January 15, 2020
Final Paper (Camera Ready) Submission & Early Bird Registration Deadline   January 11, 2020
Conference Dates   February 10 - 11, 2020

Important Notes

Please ensure your submission meets the conference's strict guidelines for accepting scholarly papers. Downloadable versions of the check list for Full-Text Papers and Abstract Papers.

Please refer to the Paper Submission GUIDE before submitting your paper.

Selected Conference Papers

1) Real-Time Episodic Memory Construction for Optimal Action Selection in Cognitive Robotics
Deon de Jager, Yahya Zweiri, Dimitrios Makris
2) Improving Fake News Detection Using K-means and Support Vector Machine Approaches
Kasra Majbouri Yazdi, Adel Majbouri Yazdi, Saeid Khodayi, Jingyu Hou, Wanlei Zhou, Saeed Saedy
3) Deep Learning Based Fall Detection Using Simplified Human Posture
Kripesh Adhikari, Hamid Bouchachia, Hammadi Nait-Charif
4) Consumer Load Profile Determination with Entropy-Based K-Means Algorithm
Ioannis P. Panapakidis, Marios N. Moschakis
5) Comparison of Machine Learning Models for the Prediction of System Marginal Price of Greek Energy Market
Ioannis P. Panapakidis, Marios N. Moschakis
6) Performance Evaluation of Distributed Deep Learning Frameworks in Cloud Environment
Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang
7) Classification of Health Risk Factors to Predict the Risk of Falling in Older Adults
L. Lindsay, S. A. Coleman, D. Kerr, B. J. Taylor, A. Moorhead
8) Predictive Semi-Empirical NOx Model for Diesel Engine
Saurabh Sharma, Yong Sun, Bruce Vernham
9) Machine Learning for Aiding Meningitis Diagnosis in Pediatric Patients
Karina Zaccari, Ernesto Cordeiro Marujo
10) An Automated Stock Investment System Using Machine Learning Techniques: An Application in Australia
Carol Anne Hargreaves
11) Fast Adjustable Threshold for Uniform Neural Network Quantization
Alexander Goncharenko, Andrey Denisov, Sergey Alyamkin, Evgeny Terentev
12) Evaluating Machine Learning Techniques for Activity Classification in Smart Home Environments
Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard
13) Noise Reduction in Web Data: A Learning Approach Based on Dynamic User Interests
Julius Onyancha, Valentina Plekhanova
14) Comparative Evaluation of Accuracy of Selected Machine Learning Classification Techniques for Diagnosis of Cancer: A Data Mining Approach
Rajvir Kaur, Jeewani Anupama Ginige
15) Missing Link Data Estimation with Recurrent Neural Network: An Application Using Speed Data of Daegu Metropolitan Area
JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

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