WELCOME TO 2023 IEEE ICCP
You are cordially invited to participate to the 2023 IEEE 19th International Conference on Intelligent Computer Communication and Processing (ICCP 2023), to be held October 26-28, 2023 in Cluj-Napoca, Romania.
At 2022 IEEE ICCP the program committee selected 43 papers for publishing from a total of 72 submissions. The papers are available in IEEE Xplore digital library and are indexed in Web Of Science and Scopus.
The goal of the 2023 IEEE 19th International Conference on Intelligent Computer Communication and Processing is to bring together researchers, engineers and practitioners working towards improving the power of both communication and processing software using the most advanced intelligent methods available today.
The growing toolkit of AI - computer vision, natural conversation, and machines that learn over time—has the potential to enhance almost the entire economic and social life. The driving forces of this development are the increased volumes of data, the continuously growing of communication, processing, storage capabilities and the new machine learning techniques especially deep learning and reinforcement learning algorithms.
The fast development of artificial intelligence and its applications implies more advanced but also more secure artifacts, which require the intelligent computer communication and processing technologies to improve at a high pace.
Technical tracks include, but are not limited to:
Agent-based and Multi-agent Systems; Knowledge Representation; Reasoning and Engineering; Ontology Modeling and Mediation; Natural Language Processing and Understanding; Web and Knowledge-based Information Systems; Multidisciplinary Topics and Applications.
CNN; RNN; GNN; Transformers; Theoretical contributions to Supervised Learning, Semi-supervised Learning, Self-supervised Learning, Unsupervised Learning, Reinforcement Learning; Neuro-symbolic Processing; Continual Learning; Synthetic Data based Learning; Explainable AI.
Deep Learning Based Computer Vision (supervised, self-supervised and unsupervised solutions):
Image Processing; Image Enhancement; Feature extraction; Semantic, Instance and Panoptic Segmentation; Optical Flow; Stereovision and 3D Reconstruction; Monocular Depth Estimation; Motion; 2D and 3D Object Detection, 3D Point Cloud Processing, Tracking and Recognition; Multi-sensor and temporal fusion; Environment Representation; Risk Assessment.
Video-based Question Answering; Driving Assistance Applications; Autonomous Vehicles; Autonomous Drones; Robotic Applications; Biomedical Image Analysis.
Intelligent Distributed Computing and Networking:
Cloud Computing, Context Aware; Autonomic Computing; Resource Coordination and Management; Quality of Service; Queuing Network Models; Pervasive Computing; Grid Computing; Fault Tolerance; Cooperative Applications.
Natural Language Understanding organized by the Computer Science Department of Technical University of Cluj-Napoca, RO.
Deep Learning Based Perception for Autonomous Systems: organized by the Technical Univeristy of Cluj-Napoca, RO.
HiPerGrid: organized in cooperation with Politehnica University, Bucharest, RO.
Smaranda Mureşan: Data Science Institute, Department of Computer Science at Columbia University.
Stefan Mathe: Sr. Embedded Machine Learning Expert at the Bosch Engineering Center Cluj.
Brainstorming On The Future Trends In Automated Driving Technology Development organized by Robert Bosch Romania, Porsche Engineering, Technical University of Cluj-Napoca, “Self Driving Automobiles” technical committee of IEEE Intelligent Transportation Society, Intelligent Vehicles Commission of the Romanian Academy.
Semantic and Geometric Visual Perception Organized by Technical University Cluj-Napoca in the framework of “DeepPerception - Deep Learning Based 3D Perception for Autonomous Driving” grant funded by Romanian Ministry of Education and Research, code PN-III-P4-PCE-2021-1134.