Moncef Gabbouj

Yuxin Peng

Kun Xu

Kun Zhou

Shi-Min Hu

Michael Elad

This three-volume set LNCS 12888, 12898, and 12890 constitutes the refereed conference proceedings of the 11th International Conference on Image and Graphics, ICIG 2021, held in Haikou, China, in August 2021.* The 198 full papers presented were selected from 421 submissions and focus on advances of theory, techniques and algorithms as well as innovative technologies of image, video and graphics processing and fostering innovation, entrepreneurship, and networking. *The conference was postponed due to the COVID-19 pandemic.

11th International Conference, ICIG 2021, Haikou, China, August 6–8, 2021, Proceedings, Part II

Image and Graphics

11th International Conference, ICIG 2021, Haikou, China, August 6–8, 2021, Proceedings, Part I

11th International Conference, ICIG 2021, Haikou, China, August 6–8, 2021, Proceedings, Part III

Klaus Schoeffmann

Thanarat H. Chalidabhongse

Chong Wah Ngo

Supavadee Aramvith

Noel E. O’Connor

Yo-Sung Ho

Ahmed Elgammal

The two-volume set LNCS 10704 and 10705 constitutes the thoroughly refereed proceedings of the 24th International Conference on Multimedia Modeling, MMM 2018, held in Bangkok, Thailand, in February 2018. Of the 185 full papers submitted, 46 were selected for oral presentation and 28 for poster presentation; in addition, 5 papers were accepted for Multimedia Analytics: Perspectives, Techniques, and Applications, 12 extended abstracts for demonstrations ,and 9 accepted papers for Video Browser Showdown 2018. All papers presented were carefully reviewed and selected from 185 submissions.

24th International Conference, MMM 2018, Bangkok, Thailand, February 5-7, 2018, Proceedings

MultiMedia Modeling

Serkan Kiranyaz

Turker Ince

For many engineering problems we require optimization processes with dynamic adaptation as we aim to establish the dimension of the search space where the optimum solution resides and develop robust techniques to avoid the local optima usually associated with multimodal problems. This book explores multidimensional particle swarm optimization, a technique developed by the authors that addresses these requirements in a well-defined algorithmic approach. After an introduction to the key optimization techniques, the authors introduce their unified framework and demonstrate its advantages in challenging application domains, focusing on the state of the art of multidimensional extensions such as global convergence in particle swarm optimization, dynamic data clustering, evolutionary neural networks, biomedical applications and personalized ECG classification, content-based image classification and retrieval, and evolutionary feature synthesis. The content is characterized by strong practical considerations, and the book is supported with fully documented source code for all applications presented, as well as many sample datasets. The book will be of benefit to researchers and practitioners working in the areas of machine intelligence, signal processing, pattern recognition, and data mining, or using principles from these areas in their application domains. It may also be used as a reference text for graduate courses on swarm optimization, data clustering and classification, content-based multimedia search, and biomedical signal processing applications.

Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition

Moncef Gabbouj

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