2023 3rd International Conference on Computer and Communication Engineering

Stockholm, Sweden 丨 March 10-12, 2023

2023 3rd International Conference on Computer and Communication Engineering (CCCE 2023) was going to take place at Stockholm, Sweden during March 10-12, 2023.

The conference co-chair, Prof. Ning Xiong (Mälardalen University, Sweden) and program chair, Prof. Jianhua Zhang (Oslo Metropolitan University, Norway) have given warmly welcome to all attendees. In addition, 3 keynote speeches was delivered by Prof. Nikola Kasabov (Auckland University of Technology, New Zealand), Prof. Angrisani Leopoldo (Università degli Studi di Napoli Federico II, Italy), Prof. Arumugam Nallanathan (Queen Mary University of London, UK). This year’s conference was composed of 3 onsite sessions and 4 online sessions, which cover a wide range of interesting topics include AI Technology and Application in Modern Information System, Model and Performance Analysis in Communication and Information Network, Machine Learning Model and Algorithm Optimization, Machine Learning Algorithm and Model Construction, Software and Information Security, Digital Image Imaging and Processing Technology & Wireless Communication and Signal Detection.

CCCE 2023 Proceedings Available Here: https://link.springer.com/book/10.1007/978-3-031-35299-7, indexed by Ei Compendex and Scopus.

The conference chair, Prof. Filippo Neri has given warmly welcome to all attendees by online. The organizing committee has invited Prof. Assaf Schuster (IEEE&ACM Fellow) from Israel Institute of Technology, Israel, Prof. Angrisani Leopoldo (IEEE Fellow) from Università degli Studi di Napoli Federico II, Italy, Prof. Dapeng Wu (IEEE Fellow) from University of Florida, USA and Prof. Ning Xiong from Mälardalen University, Sweden to deliver keynote&plenary speeches. They have given topics with "Complex Events in Massive Data Streams", "Artificial Intelligence and Measurement Science: A Synergetic Interaction for the 4.0 Era and the (r)evolution into Cyber-Physical Measurement Systems" "One-shot Federated Learning for Communication Reduction and Model Compression" “Enhancing Differential Evolution with Integrated Adaption and Local Search” seperately.