Calls for Papers

Authors are invited to submit electronically original, English-language research contributions or experience reports not concurrently submitted elsewhere. The Proceedings of the 23rd EANN 2022 will be published in the SPRINGER Lecture Notes in Computer Science (LNCS) Communications in Computer and Information Science CCIS book series and IINDEXED to the Conference Proceedings Citation Index (CPCI) – part of Clarivate Analytics’ Web of Science, EI Engineering Index (Compendex and Inspec databases), ACM Digital Library, DBLP, Google Scholar, IO-Port, MathSciNet, Scopus and Zentralblatt MATH. For more information visit the following Springer Link: https://www.springer.com/series/7899 Papers should be no longer than 12 pages formatted according to the LNCS Springer style. The program committee may reject papers that exceed this length on the grounds of length alone. In the spirit of the previous EANN conferences, the paper should concentrate on the application rather than just the algorithm or the theory. Submitted papers will be refereed by at least three reviewers for quality, correctness, originality, and relevance. Notification and reviews will be communicated via email.  It is important though to follow the instructions in this page to ensure that your paper will be included in the proceedings. Camera-ready submissions should be corrected by following the remarks of the referees and submitted in zip format including (1) the camera-ready version of the authors’ work in pdf format, (2) the camera-ready version of the authors’ work in editable sources format as well as (3) the Consent to Publish signed in ink and scanned to image file. The results described must be unpublished and must not be under review elsewhere. Submissions must conform to Springer’s LNCS format and should be, including all text, figures, references and appendices: 12 pages for papers accepted as full and 10 pages for papers accepted as short. Topics are related but not restricted to:

• Artificial Neural Networks Spiking
• Artificial Neural Networks (Multi Layer FF)
• Accessibility and Computers
• Adaptive AI architectures
• Adaptive Control
• Affective Computing
• Agent and Multi-Agent Systems
• AI and Ethical Issues
• Artificial Intelligence Applications
• Autonomous and Ubiquitous Computing
• Bayesian and Echo State Networks
• Bayesian Models
• Bioinformatics
• Biologically Inspired Neural Networks
• Biomedical systems
• Coding Architectures Interacting with The Brain
• Collective Computational Intelligence
• Colour/Image Analysis
• Complex Firing Patterns
• Computational Intelligence
• Computer Vision
• Convolutional Neural Networks
• Crisis and Risk Management
• Cybersecurity and AI
• Data Fusion
• Data Mining and Information Retrieval
• Decision Support Systems
• Deep Learning
• Deep Learning and Big Data
• Deep Learning and Big Data Analytics
• Deep Learning and Cybersecurity
• Deep Learning and Forensics
• Deep Learning and Real Time Systems
• Deep Learning and Social Networks
• Dimensionality Reduction
• Distributed AI Systems and Architectures
• eBusiness, eCommerce, eHealth, eLearning
• Education Intelligent Tutoring
• Emerging Applications
• Engineering and Industry
• Environmental Modelling
• Evaluation of AI Systems
• Evolving Systems – Optimization
• Expert Systems
• Filtering
• Finance
• Forensic Science
• From Neurons to Neuromorphism
• From Sensation to Perception
• From Single Neurons to Networks
• Fusion
• Fuzzy Logic and Systems
• General Engineering AI Applications
• Genetic Algorithms and Programming
• Grid-Based Computing
• Human-Machine Interaction / Presence
• Hybrid Intelligent systems
• Information and Optimization
• Intelligence
• Intelligent
• Information Systems
• Intelligent Music Mining
• Intelligent Profiling and Personalisation
• Intelligent Transportation Systems
• Internet of Things (IoT)
• Kernel Systems
• Knowledge Acquisition and Representation
• Knowledge Engineering
• Knowledge Management for e-Learning and Enterprise Portals
• Learning
• Learning and Adaptive Systems
• Machine Learning
• Machine Learning and Cybersecurity
• Machine Learning and Forensics
• Machine Learning and Social
• Machine Learning and Video – Image Processing
• Machine Learning for BioMedical systems
• Mathematical Foundations of AI and Intelligent Computational methods
• Media Machine Learning in Engineering
• Medical Informatics and Biomedical
• Movement and Motion
• Multi agent systems
• Multi Layer Perceptrons
• Multilayer Perceptrons and Kernel Networks
• Multimedia Computing
• Multimedia Ontologies
• Multimedia, Graphics and Artificial Natural Language Processing
• Object and Face Recognition
• Ontologies
• Other
• Particle Swarm Optimisation
• Pattern Recognition
• Planning and Resource Management
• Planning and Scheduling
• Political Decision Making
• Process Monitoring and Diagnosis
• Project Management
• Reasoning Methods
• Recommendation Systems
• Recurrent Neural Networks and Reservoir Computing
• Risk Modeling
• Robotics
• Robotics and Virtual Reality
• Self Organizing Maps
• Signal and Image Processing
• Signal Processing Techniques and  Knowledge Extraction
• Smart Cities
• Smart Graphics
• Smart Grids
• Social Impact of AI
• Social Media and AI
• Speech and Natural Language Processing
• Speech Synthesis
• Spiking Dynamics
• Support Vector Machines
• Swarm Intelligence and Decision-Making
• Telecommunications – Transportation
• Text Mining
• Theoretical Neural Computation
• Time Series and Forecasting
• Training and Learning Inference and Recognition Clustering, Mining and Exploratory Analysis
• Trends in Computing
• Unsupervised Machine Learning
• Web and Knowledge-Based Information Systems