MDCWC2020: Machine learning, Deep learning and Computational Intelligence for wireless communication (MDCWC2020) National Institute of Technology Tiruchirappalli Tiruchirappalli, India, October 22-24, 2020 |
Conference website | https://mdcwc2020.yolasite.com/ |
Submission link | https://easychair.org/conferences/?conf=mdcwc2020 |
Poster | download |
Submission deadline | September 10, 2020 |
Workshop on Machine learning, Deep learning and Computational Intelligence for wireless communication (MDCWC2020): 22nd October to 24th October 2020
Due to the feasibility of collecting huge data from mobile and wireless networks, there are many possibilities of using Machine learning, Deep-learning and the Computational Intelligence to interpret and to hunt knowledge from the collected data. The workshop aims in consolidating the experimental results integrating the Machine learning, Deep learning and Computational intelligence for wireless communication. The workshopfocus on the following applications.
Mobile data analysis, Mobility analysis, Network control and security, Wireless sensor networks, User localization, Mobile Network and Signal processing. Also those applications are implemented using one or more of the following ML, DL and Computational intelligence algorithms like the following.
Machine learning: Multiple input Multiple output regression, Probabilistic discriminative approach, Multi-class logistic regression, Probabilistic generative model, Support Vector Machine, Dimensionality reduction techniques. Deep learning: Multilayer perceptron, Boltzmann Machine, Auto-Encoders, Convolutional Neural Network, Recurrent Neural Network, Generative Adversarial Network, Deep Reinforcement Learning. Computational Intelligence: Particle Swarm Optimization, Bacterial Foraging, Simulated Annealing, Ant colony technique, Genetic algorithm, Social Emotional Optimization Algorithm (SEOA), Social Evolutionary Learning Algorithm (SELA).
About the workshop
Scope of the workshop: The workshop acts as the platform to disseminate the new discovery to reach the world through high quality publications for the research scholars. This also helps to see others contribution, which in further helps in finding new directions in their research.
Who should submit and present?
Beginner research scholars those who are doing research in Machine Learning, Deep learning and Computational intelligence for wireless communication
Post Graduate students who are doing project as the part of the curriculum.
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference.
The papers are expected in the following data driven Wireless Communication Applications (Not limited to)
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Network prediction, Traffic classification, Call detail record mining.
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Mobile health care, Mobile pattern recognition, Natural language processing, Automatic Speech Processing
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Mobility analysis, Indoor localization
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Wireless Sensor Networks (WSN)
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Energy minimization, Routing, Scheduling, Resource allocation, Multiple access, Power control
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Malware detection, Cyber security , Flooding attacks detection, Mobile apps sniffing
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MIMO detection, Signal detection in MIMO-OFDM, Modulation recognition, Channel estimation, MIMO nonlinear equalization, Super -resolution channel and direction-of-arrival estimation, NOMA, mm-wave channel model,Full duplex,OFDM/FBMC,NB-IOT
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Template for preparing the papers https://www.springer.com/us/authors-editors/conference-proceedings/conference-proceedings-guidelines
Publication
The submissions are subjected to Double review process and the selected papers will be published as the book series Lecture Notes in Electrical Engineering, Springer publication (Confirmed). https://www.springer.com/series/7818
Important dates
https://www.nitt.edu/home/ECE_MDCWC_2020-v11.pdf
Last date of submission:31st August 2020
(Through Easy Chair) https://easychair.org/my/conference?conf=mdcwc2020:
Contact
Dr.E.S.Gopi
Associate professor
Department of Electronics and Communication Engineering
National Institute of Technology Tiruchirappalli
esgopi@nitt.edu
Mobile:914312503314