Open Science Research Excellence

ICSPC 2020 : International Conference on Signal Processing and Communications

San Francisco, USA
November 2 - 3, 2020

Conference Code: 20US11ICSPC

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

ICSPC 2020 has teamed up with the Special Journal Issue on Signal Processing and Communications. 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   January 30, 2020
Notification of Acceptance/Rejection   February 13, 2020
Final Paper (Camera Ready) Submission & Early Bird Registration Deadline   October 2, 2020
Conference Dates   November 2 - 3, 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) Deep Learning Based Fall Detection Using Simplified Human Posture
Kripesh Adhikari, Hamid Bouchachia, Hammadi Nait-Charif
2) Consumer Load Profile Determination with Entropy-Based K-Means Algorithm
Ioannis P. Panapakidis, Marios N. Moschakis
3) The Principle Probabilities of Space-Distance Resolution for a Monostatic Radar and Realization in Cylindrical Array
Anatoly D. Pluzhnikov, Elena N. Pribludova, Alexander G. Ryndyk
4) Comparison of Machine Learning Models for the Prediction of System Marginal Price of Greek Energy Market
Ioannis P. Panapakidis, Marios N. Moschakis
5) From Electroencephalogram to Epileptic Seizures Detection by Using Artificial Neural Networks
Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone
6) Performance Evaluation of Distributed Deep Learning Frameworks in Cloud Environment
Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang
7) A Generalized Sparse Bayesian Learning Algorithm for Near-Field Synthetic Aperture Radar Imaging: By Exploiting Impropriety and Noncircularity
Pan Long, Bi Dongjie, Li Xifeng, Xie Yongle
8) Predictive Semi-Empirical NOx Model for Diesel Engine
Saurabh Sharma, Yong Sun, Bruce Vernham
9) 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
10) Changes in Student Definition of De-Escalation in Professional Peace Officer Education
Pat Nelson
11) Machine Learning for Aiding Meningitis Diagnosis in Pediatric Patients
Karina Zaccari, Ernesto Cordeiro Marujo
12) An Automated Stock Investment System Using Machine Learning Techniques: An Application in Australia
Carol Anne Hargreaves
13) Fast Adjustable Threshold for Uniform Neural Network Quantization
Alexander Goncharenko, Andrey Denisov, Sergey Alyamkin, Evgeny Terentev
14) Evaluating Machine Learning Techniques for Activity Classification in Smart Home Environments
Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard
15) Noise Reduction in Web Data: A Learning Approach Based on Dynamic User Interests
Julius Onyancha, Valentina Plekhanova

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