In Computer Graphics, the use of intelligent techniques started more recently than in other research areas. However, during these last two decades, the use of intelligent Computer Graphics techniques is growing up year after year and more and more interesting techniques are presented in this area. The purpose of this volume is to present current work of the Intelligent Computer Graphics community, a community growing up year after year. This volume is a kind of continuation of the previously published Springer volumes “Artificial Intelligence Techniques for Computer Graphics” (2008), “Intelligent Computer Graphics 2009” (2009) and “Intelligent Computer Graphics 2010” (2010). This volume contains selected extended papers from the last 3IA Conference (3IA’2011), which has been held in Athens (Greece) in May 2011. This year papers are particularly exciting and concern areas like virtual reality, artificial life, data visualization, games, global illumination, point cloud modelling, declarative modelling, scene reconstruction and many other very important themes.

In Computer Graphics, the use of intelligent techniques started more recently than in other research areas. However, during these last two decades, the use of intelligent Computer Graphics techniques is growing up year after year and more and more interesting techniques are presented in this area. The purpose of this volume is to present current work of the Intelligent Computer Graphics community, a community growing up year after year. This volume is a kind of continuation of the previously published Springer volumes “Artificial Intelligence Techniques for Computer Graphics” (2008), “Intelligent Computer Graphics 2009” (2009), “Intelligent Computer Graphics 2010” (2010) and “Intelligent Computer Graphics 2011” (2011). Usually, this kind of volume contains, every year, selected extended papers from the corresponding 3IA Conference of the year. However, the current volume is made from directly reviewed and selected papers, submitted for publication in the volume “Intelligent Computer Graphics 2012”. This year papers are particularly exciting and concern areas like plant modelling, text-to-scene systems, information visualization, computer-aided geometric design, artificial life, computer games, realistic rendering and many other very important themes.

In Computer Graphics, the use of intelligent techniques started more recently than in other research areas. However, during these last two decades, the use of intelligent Computer Graphics techniques is growing up year after year and more and more interesting techniques are presented in this area. The purpose of this volume is to present current work of the Intelligent Computer Graphics community, a community growing up year after year. This volume is a kind of continuation of the previously published Springer volumes “Artificial Intelligence Techniques for Computer Graphics” (2008), “Intelligent Computer Graphics 2009” (2009) and “Intelligent Computer Graphics 2010” (2010). This volume contains selected extended papers from the last 3IA Conference (3IA’2011), which has been held in Athens (Greece) in May 2011. This year papers are particularly exciting and concern areas like virtual reality, artificial life, data visualization, games, global illumination, point cloud modelling, declarative modelling, scene reconstruction and many other very important themes.

Supervised sequence labelling is a vital area of machine learning, encompassing tasks such as speech, handwriting and gesture recognition, protein secondary structure prediction and part-of-speech tagging. Recurrent neural networks are powerful sequence learning tools—robust to input noise and distortion, able to exploit long-range contextual information—that would seem ideally suited to such problems. However their role in large-scale sequence labelling systems has so far been auxiliary. The goal of this book is a complete framework for classifying and transcribing sequential data with recurrent neural networks only. Three main innovations are introduced in order to realise this goal. Firstly, the connectionist temporal classification output layer allows the framework to be trained with unsegmented target sequences, such as phoneme-level speech transcriptions; this is in contrast to previous connectionist approaches, which were dependent on error-prone prior segmentation. Secondly, multidimensional recurrent neural networks extend the framework in a natural way to data with more than one spatio-temporal dimension, such as images and videos. Thirdly, the use of hierarchical subsampling makes it feasible to apply the framework to very large or high resolution sequences, such as raw audio or video. Experimental validation is provided by state-of-the-art results in speech and handwriting recognition.

This monograph presents selected areas of application of pattern recognition and classification approaches including handwriting recognition, medical image analysis and interpretation, development of cognitive systems for image computer understanding, moving object detection, advanced image filtration and intelligent multi-object labelling and classification. It is directed to the scientists, application engineers, professors, professors and students will find this book useful.

This book is a selection of results obtained within one year of research performed under SYNAT - a nation-wide scientific project aiming to create an infrastructure for scientific content storage and sharing for academia, education and open knowledge society in Poland. The selection refers to the research in artificial intelligence, knowledge discovery and data mining, information retrieval and natural language processing, addressing the problems of implementing intelligent tools for building a scientific information platform. The idea of this book is based on the very successful SYNAT Project Conference and the SYNAT Workshop accompanying the 19th International Symposium on Methodologies for Intelligent Systems (ISMIS 2011). The papers included in this book present an overview and insight into such topics as architecture of scientific information platforms, semantic clustering, ontology-based systems, as well as, multimedia data processing.

The book is a collection of invited papers on Computational Intelligence for Privacy and Security. The majority of the chapters are extended versions of works presented at the special session on Computational Intelligence for Privacy and Security of the International Joint Conference on Neural Networks (IJCNN-2010) held July 2010 in Barcelona, Spain. The book is devoted to Computational Intelligence for Privacy and Security. It provides an overview of the most recent advances on the Computational Intelligence techniques being developed for Privacy and Security. The book will be of interest to researchers in industry and academics and to post-graduate students interested in the latest advances and developments in the field of Computational Intelligence for Privacy and Security.

The goal of Intelligent video surveillance systems is to efficiently extract useful information from a considerable number of videos collected by surveillance cameras by automatically detecting, tracking and recognizing objects of interest, and understanding and analyzing their activities. Video surveillance has a huge amount of applications, from public to private places. These applications require monitoring indoor and outdoor scenes. Nowadays, there are a considerable number of digital surveillance cameras collecting a huge amount of data on a daily basis. Researchers are urged to develop intelligent systems to efficiently extract and visualize useful information from this big data source. The exponential effort on the development of new algorithms and systems for video surveillance is confirmed by the amount of effort invested in projects and companies, the creation on new startups worldwide and, not less important, in the quantity and quality of the manuscripts published in a considerable number of journals and conferences worldwide. This book is an outcome of research done by several researchers who have highly contributed to the field of Video Surveillance. The main goal is to present recent advances in this important topic for the Image Processing community.

This book – in conjunction with the volumes LNAI 8589 and LNBI 8590 – constitutes the refereed proceedings of the 10th International Conference on Intelligent Computing, ICIC 2014, held in Taiyuan, China, in August 2014. The 92 papers of this volume were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections such as evolutionary computation and learning; swarm intelligence and optimization; machine learning; social and natural computing; neural networks; biometrics recognition; image processing; information security; virtual reality and human-computer interaction; knowledge discovery and data mining; signal processing; pattern recognition; biometric system and security for intelligent computing.

This book includes original, peer-reviewed articles from the 2nd International Conference on Cognitive & Intelligent Computing (ICCIC-2022), held at Vasavi College of Engineering Hyderabad, India. It covers the latest trends and developments in areas of cognitive computing, intelligent computing, machine learning, smart cities, IoT, artificial intelligence, cyber-physical systems, cybernetics, data science, neural network, and cognition. This book addresses the comprehensive nature of computational intelligence, cognitive computing, AI, ML, and DL to emphasize its character in modeling, identification, optimization, prediction, forecasting, and control of future intelligent systems. Submissions are original, unpublished, and present in-depth fundamental research contributions either from a methodological/application perspective in understanding artificial intelligence and machine learning approaches and their capabilities in solving diverse range of problems in industries and its real-world applications.