This International Conference on Artificial Intelligence in Electronics and Communication (AELCOMM-2023), is dedicated to advanced research in the use of artificial intelligence for design of electronic and communication systems. The past few decades witnessed rapid developments in the design of electronic circuits and communication networks. Artificial intelligence has played an important role in this and its ubiquitous influence is increasing in solving real life problems. Evolutionary optimization techniques, machine learning, artificial intelligence, neural networks, deep learning, etc. are helping the researchers to explore previously uncharted areas and to push forward the frontiers of science and technology. The conference aims at bringing together the researchers, scientists, engineers and research scholars from all areas of engineering and technology, to provide an international forum to exchange their ideas, foster collaboration, practical developments experiences and cover new grounds. The conference will feature invited talks by eminent researchers from around the world, technical paper sessions, poster sessions, demos, tutorials and workshops. It is planned to publish the proceedings with Springer in their and other databases. Prospective authors are encouraged to submit their original research contributions in Springer CCIS series format.
“ Topics of Interest include (But are not limited to)”
Machine learning for Signal Processing, Deep learning techniques, Applications in Medical Imaging, Bio-medical signal processing, Remote sensing applications, Algorithms for Speech Recognition and Speech Processing, Image processing, Evolutionary algorithms for signal processing applications
Artificial Intelligence in Communication, 5G and 6G Communication Networks, Vehicular networks, Internet of Things, Enhanced Network Security Using Machine Learning, Cryptography Techniques Using Machine Learning, Wireless Sensor Networks, Smart Grid, LoRa, MIMO techniques, Deep learning and machine learning techniques for 4G and 5G, OFDM, extreme learning techniques and one-shot learning, for real-time applications, reinforcement learning for 5G and 6G, Blockchain and lightweight blockchains for distributed applications.
Embedded AI, Deep learning and Machine learning for Embedded Vision, Machine Vision, Intelligent embedded systems, AI for autonomous embedded systems, Optimization of VLSI Designs, Optimization of Circuits, Optimization in Embedded System, Design of High Performance Systems
AI for Power Electronics; AI for power converters; AI for Industry 4.0; AI for Smart Grid; Intelligent instrumentation; Intelligent sensors; AI for robotics; PID controllers; Load frequency control; Microgrid; Deep learning and machine learning energy management; Battery modeling; AI for power system.
Deep learning for electromagnetics; direction of arrival estimation; Antenna array synthesis; deep learning for inverse scattering problems; design of antennas; metamaterials; Terahertz sensing and imaging;