Excellence in Research and Innovation for Humanity

ICCSP 2021 : 23rd International Conference on Communications and Signal Processing

Singapore, SG
January 8 - 9, 2021

Conference Code: 21SG01ICCSP

Conference Proceedings

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

Special Journal Issues

ICCSP 2021 has teamed up with the Special Journal Issue on Communications and Signal Processing. 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 8, 2020
Notification of Acceptance/Rejection   October 8, 2020
Final Paper (Camera Ready) Submission & Early Bird Registration Deadline   December 8, 2020
Conference Dates   January 8 - 9, 2021

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) Noise Reduction in Web Data: A Learning Approach Based on Dynamic User Interests
Julius Onyancha, Valentina Plekhanova
2) 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
3) Evaluating Machine Learning Techniques for Activity Classification in Smart Home Environments
Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard
4) Cognition of Driving Context for Driving Assistance
Manolo Dulva Hina, Clement Thierry, Assia Soukane, Amar Ramdane-Cherif
5) Road Vehicle Recognition Using Magnetic Sensing Feature Extraction and Classification
Xiao Chen, Xiaoying Kong, Min Xu
6) Hybrid Reliability-Similarity-Based Approach for Supervised Machine Learning
Walid Cherif
7) Comparative Evaluation of Accuracy of Selected Machine Learning Classification Techniques for Diagnosis of Cancer: A Data Mining Approach
Rajvir Kaur, Jeewani Anupama Ginige
8) Hybrid Approach for Software Defect Prediction Using Machine Learning with Optimization Technique
C. Manjula, Lilly Florence
9) Relay Node Placement for Connectivity Restoration in Wireless Sensor Networks Using Genetic Algorithms
Hanieh Tarbiat Khosrowshahi, Mojtaba Shakeri
10) Early Diagnosis of Alzheimer's Disease Using a Combination of Images Processing and Brain Signals
E. Irankhah, M. Zarif, E. Mazrooei Rad, K. Ghandehari
11) Optimized Preprocessing for Accurate and Efficient Bioassay Prediction with Machine Learning Algorithms
Jeff Clarine, Chang-Shyh Peng, Daisy Sang
12) Hand Gesture Detection via EmguCV Canny Pruning
N. N. Mosola, S. J. Molete, L. S. Masoebe, M. Letsae
13) Improving Similarity Search Using Clustered Data
Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong
14) Adaption Model for Building Agile Pronunciation Dictionaries Using Phonemic Distance Measurements
Akella Amarendra Babu, Rama Devi Yellasiri, Natukula Sainath
15) A Comprehensive Evaluation of Supervised Machine Learning for the Phase Identification Problem
Brandon Foggo, Nanpeng Yu

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