1. COMPUTATIONAL INTELLIGENCE FOR ENHANCED AGENT-BASED MODELS 

2. 
ARTIFICIAL NEURAL NETWORKS FOR COMPUTER AND ROBOT VISION

3.  HYBRID MACHINE LEARNING ALGORITHMS AND APPLICATIONS  

4. WEB AND SOCIAL MEDIA

5. COMPUTATIONAL INTELLIGENCE IN REMOTE SENSING DATA ANALYSIS

The special session will aim at providing a leading international forum to bring together researchers and practitioners from diverse fields, such as computer science, information technology, business, education, human factors, systems engineering, and robotics. The session will aim at examining the design principles and performance characteristics of various approaches in agent-based technology among many different domains, such as surveillance, monitoring, IoT, earth observations and any agent-oriented design systems; At the same time, it will aim at increasing the cross-fertilization of ideas on the development of autonomous agents and multi-agent systems by Computational Intelligence models.

By encouraging idea-sharing and discussions on the underlying logical, cognitive, physical, and sociological foundations as well as the enabling technologies of intelligent agents, the Special Session will foster the development of novel paradigms and advanced solutions in agent-based systems by Computational Intelligence techniques. This Symposium aims at bringing researchers and users from academia and industry together to report, interact and review the latest progress in this field, to explore future directions of research to a wider audience from diverse fields joining the ICECTI in Hyderabad, India and beyond.

Topics

This Special Session will bring together researchers from both industry and academia from the various disciplines contributing to the area on intelligent agents. Such disciplines include, but are not limited to:

Autonomous Knowledge and Information Agents
Agent-based Unmanned Vehicles
Agent Systems Modeling and Methodology
Autonomous Auctions and Negotiation
Agent-Based Marketplaces
Agents for E-Commerce
Agent-Based Data Mining
Multi-agent UAV Swarm
Agents for Dialogue Systems
Swarm Intelligence for cooperative and coordinative tasks
Unmanned Vehicles and Multi UV systems
Agents for IoT
Fuzzy model for Context-Aware process execution
Fuzzy model for enhanced multi-source environments
Situational/Context Awareness
Surveillance and Monitoring
Intelligent Agents
Environment-aware Agents
Fuzzy cognitive Maps for reasoning
Fuzzy semantic Web
Fuzzy clustering models
Sensing Technology
Data Fusion in Ubiquitous Environments
Control systems for multi-sensing environment
Multi-Agent Planning
Consensus decision making solutions
Ubiquitous computing
Pervasive computing
Computational Social Science
Smart Evolving Sensors
Autonomous Knowledge and Information Agents
Semantic Web Agents
Human Agent Interaction
Agents for Smart Environments
Social Interactions in Multi-Agent Systems
Agents Applications

Organizer
Sabrina Senatore – Associate Professor, University of Salerno (Italy)

Artificial Neural Networks have been used in many analysis problems due to their ability to approximate complex functions and relationships following a data-driven learning paradigm. Recent developments in end-to-end learning methodologies based on deep Artificial Neural Network architectures led to remarkable performance improvements in visual information analysis. Nowadays, Multilayer Perceptrons, Convolutional Neural Networks, Recurrent Neural Networks and Graph Neural Networks are the de-facto choices for a variety of problems coming from Computer and Robot Vision fields. However, state-of-the-art ANN-based systems need training on large-scale annotated datasets, and require an enormous number of computations and high memory being available only in specialized computing hardware, like high-end Graphical Processing Units and parallel computational systems. Thus, adoption of such high-performing ANN-based solutions in real-life Computer and Robotic Vision problems in general is limited.

Topics

The purpose of the Special Session is to provide a forum to exchange ideas and to discuss developments in Artificial Neural Networks with applications in Computer and Robot Vision. Topics of interest include (but are not limited to):

ANNs for person/face/object detection and recognition
ANNs for 2D/3D object localization and tracking
ANNs for facial expression recognition and affective computing
ANNs for human actions and gestures recognition
ANNs for audio and speech analysis and recognition
ANNs for semantic scene analysis and understanding
ANNs for visual odometry
Robust ANN methodologies for real-life Computer and Robot Vision systems
Efficient ANN architectures for Computer and Robotic Vision systems
ANNs for end-to-end planning and navigation
Efficient ANN training on medium/small-scale data
Neural Architecture Search and Progressive Neural Network training
Compressive Sensing and Compressive Learning with ANNs
ANN methods for efficient IoT-based Robotic Vision applications

The Special Session is supported by the H2020 project OpenDR.

Organizer

Alexandros Iosifidis, Associate Professor, Aarhus University, Aarhus, Denmark

Soft Computing (SC) methodologies include Neural Networks, Fuzzy Logic, Evolutionary Algorithms, and Chaos Theory, etc. Each of these methodologies has advantages and disadvantages. Despite this, many problems have been solved using these methodologies. However, many real-world complex and industrial problems require the integration of several of these techniques to achieve the efficiency and accuracy needed in practice. This session will include papers dealing with methods integrating different SC methodologies for solving real-world problems. The Special Session will consider hybrid machine learning algorithms and their applications in the following areas: Disease Diagnosis, Non-linear data Classification, Pattern Recognition, Image Recognition, etc. Hybrid machine learning algorithms offer advantages when a prudent combination of methods is performed, and in this case, can be a powerful tool in solving complex problems and real-life applications.

Topics

This special session aims to promote research on hybrid machine learning algorithms all over the world and provides innovative approaches for solving real-life problems. The scope of this special session covers the following topics but not limited to these topics:

Hybrid Neural Systems
Neuro-Fuzzy Systems
Evolutionary Neural Systems
Neuro Fuzzy Evolutionary Systems
Quantum Neural Network
Hybrid Intelligent models and their application on Pattern Recognition, Disease Diagnosis, Image Recognition, Non-linear Data Classification, and many more.

Organizers

Dr. Om Prakash Patel, Assistant Professor, Department of Computer Science and Engineering,
École Centrale School of Engineering, Mahindra University, Hyderabad, Telangana, India

Dr. Dheeraj Rane, Associate Professor, Department of Computer Science and Engineering,
Medi-Caps University, Indore, India.

The special session is organized around the common theme of analyzing human social behavior on web and online social media. The focus will be answering the important and challenging question on human social behavior using the vast amount of data available on web and social media platforms. The special session will be a forum for interdisciplinary researchers and practitioners from diverse fields such as social sciences, economics and computer science. Submissions are encouraged on computational approaches to social media research including natural language processing, data mining, text mining, and network science.

Topics

The scope of this special session covers the following topics but not limited to these topics:

Qualitative and quantitative studies of social media
Ranking/relevance of social media content and users
Credibility of online content including fake news detection
Social network analysis
Recommendation systems
Sentiment analysis
Natural language processing applied to social media
Viral content identification and tracking; time series forecasting
Prediction of real-world phenomena based on social media
Engagement, motivations, incentives, and gamification
Live online social media
Social innovation and effecting change through social media
Social media usage on mobile devices; impact on wireless communication
Herd behavior in social media

Organizer

Dr. Anup Aprem, Assistant Professor, Department of Electronics and Communication Engineering,
National Institute of Technology Calicut

The recent time has witnessed an enormous volume of remote sensing data using airborne and space-borne sensors. The general objective is to provide large-scale, homogeneous information processing from these data. The sheer volume of these multi-modal data sources needs highly- automated and intelligent frameworks. The resurgence of deep neural networks has popularized Computational Intelligence (CI) techniques. They have found wide applications in the land- cover/land-use classification, content-based data retrieval, region-detection, and temporal analysis of remote sensing data. Due to the availability of many satellite missions, certain multi- modal approaches like data fusion for pan-sharpening and colorization problems, and cross- modal data retrieval be of extreme importance. Earth observation tasks also imply the need for various location-based services, online mapping services, surveillance, crop-monitoring, soil- moisture tracking, various forms of change detection applications, to name a few. This special session aims to bring together researchers working in developing CI techniques for remote sensing data analysis and providing a forum for discussion on the above topics.

Topics

We invite submission in the following remote sensing data analysis areas but not limited to the following topics:

Image classification, segmentation and clustering
UAV data analysis
Multi-modal data fusion and classification
Supervised and unsupervised learning
Spectral and spatial methods
Spectral unmixing
Image understanding and synthesis
Noise filtering
Change detection
Time series analysis
Geo-intelligence
Target detection

Organizers

Dr. Avik Bhattacharya, Associate Professor, Centre of Studies in Resources Engineering,
Indian Institute of Technology Bombay

Dr. Mihai Datcu, Professor with the Department of Applied Electronics and Information Engineering,
Telecommunications and Information Technology, UPB