Scholarly Research Excellence

ICMLT 2018 : 20th International Conference on Machine Learning and Technology

Singapore, SG
September 10 - 11, 2018

Conference Code: 18SG09ICMLT

Conference Proceedings

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

Special Journal Issues

ICMLT 2018 has teamed up with the Special Journal Issue on Machine Learning and Technology. 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   July 20, 2018
Notification of Acceptance/Rejection   July 31, 2018
Final Paper (Camera Ready) Submission & Early Bird Registration Deadline   August 10, 2018
Conference Dates   September 10 - 11, 2018

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) Prediction on Housing Price Based on Deep Learning
Li Yu, Chenlu Jiao, Hongrun Xin, Yan Wang, Kaiyang Wang
2) Noise Reduction in Web Data: A Learning Approach Based on Dynamic User Interests
Julius Onyancha, Valentina Plekhanova
3) 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
4) Evaluating Machine Learning Techniques for Activity Classification in Smart Home Environments
Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard
5) Cognition of Driving Context for Driving Assistance
Manolo Dulva Hina, Clement Thierry, Assia Soukane, Amar Ramdane-Cherif
6) Long Short-Term Memory Based Model for Modeling Nicotine Consumption Using an Electronic Cigarette and Internet of Things Devices
Hamdi Amroun, Yacine Benziani, Mehdi Ammi
7) Hybrid Reliability-Similarity-Based Approach for Supervised Machine Learning
Walid Cherif
8) Comparative Evaluation of Accuracy of Selected Machine Learning Classification Techniques for Diagnosis of Cancer: A Data Mining Approach
Rajvir Kaur, Jeewani Anupama Ginige
9) Mix Proportioning and Strength Prediction of High Performance Concrete Including Waste Using Artificial Neural Network
D. G. Badagha, C. D. Modhera, S. A. Vasanwala
10) Hybrid Approach for Software Defect Prediction Using Machine Learning with Optimization Technique
C. Manjula, Lilly Florence
11) Automatic Classification of Periodic Heart Sounds Using Convolutional Neural Network
Jia Xin Low, Keng Wah Choo
12) ELISA Based hTSH Assessment Using Two Sensitive and Specific Anti-hTSH Polyclonal Antibodies
Maysam Mard-Soltani, Mohamad Javad Rasaee, Saeed Khalili, Abdol Karim Sheikhi, Mehdi Hedayati
13) Application of ANN for Estimation of Power Demand of Villages in Sulaymaniyah Governorate
A. Majeed, P. Ali
14) Optimized Preprocessing for Accurate and Efficient Bioassay Prediction with Machine Learning Algorithms
Jeff Clarine, Chang-Shyh Peng, Daisy Sang
15) Crude Oil Price Prediction Using LSTM Networks
Varun Gupta, Ankit Pandey

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