Computer Vision -- ECCV 2014


Book Description

The seven-volume set comprising LNCS volumes 8689-8695 constitutes the refereed proceedings of the 13th European Conference on Computer Vision, ECCV 2014, held in Zurich, Switzerland, in September 2014. The 363 revised papers presented were carefully reviewed and selected from 1444 submissions. The papers are organized in topical sections on tracking and activity recognition; recognition; learning and inference; structure from motion and feature matching; computational photography and low-level vision; vision; segmentation and saliency; context and 3D scenes; motion and 3D scene analysis; and poster sessions.




Computational Intelligence Methods for Super-Resolution in Image Processing Applications


Book Description

This book explores the application of deep learning techniques within a particularly difficult computational type of computer vision (CV) problem ─ super-resolution (SR). The authors present and discuss ways to apply computational intelligence (CI) methods to SR. The volume also explores the possibility of using different kinds of CV techniques to develop and enhance the tools/processes related to SR. The application areas covered include biomedical engineering, healthcare applications, medicine, histology, and material science. The book will be a valuable reference for anyone concerned with multiple multimodal images, especially professionals working in remote sensing, nanotechnology and immunology at research institutes, healthcare facilities, biotechnology institutions, agribusiness services, veterinary facilities, and universities.




Image Analysis and Processing – ICIAP 2019


Book Description

The two-volume set LNCS 11751 and 11752 constitutes the refereed proceedings of the 20th International Conference on Image Analysis and Processing, ICIAP 2019, held in Trento, Italy, in September 2019. The 117 papers presented were carefully reviewed and selected from 207 submissions. The papers cover both classic and the most recent trends in image processing, computer vision, and pattern recognition, addressing both theoretical and applicative aspects. They are organized in the following topical sections: Video Analysis and Understanding; Pattern Recognition and Machine Learning; Deep Learning; Multiview Geometry and 3D Computer Vision; Image Analysis, Detection and Recognition; Multimedia; Biomedical and Assistive Technology; Digital Forensics; Image processing for Cultural Heritage.




ICT Innovations 2015


Book Description

This book offers a collection of selected papers presented at the Seventh International Conference on ICT Innovations held in October 2015, in Ohrid, Macedonia, with main topic Emerging Technologies for Better Living. The conference gathered academics, professionals and industrial practitioners that work on developing the emerging technologies, systems, applications in the industrial and business arena especially innovative commercial implementations, novel application of technology, and experience in applying recent ICT research advances to practical solutions.




Advanced Deep Learning Methods for Biomedical Information Analysis (ADLMBIA)


Book Description

Due to numerous biomedical information sensing devices, such as Computed Tomography (CT), Magnetic Resonance (MR) Imaging, Ultrasound, Single Photon Emission Computed Tomography (SPECT), and Positron Emission Tomography (PET), to Magnetic Particle Imaging, EE/MEG, Optical Microscopy and Tomography, Photoacoustic Tomography, Electron Tomography, and Atomic Force Microscopy, etc. a large amount of biomedical information was gathered these years. However, identifying how to develop new advanced imaging methods and computational models for efficient data processing, analysis and modelling from the collected data is important for clinical applications and to understand the underlying biological processes. Deep learning approaches have been rapidly developed in recent years, both in terms of methodologies and practical applications. Deep learning techniques provide computational models of multiple processing layers to learn and represent data with multiple levels of abstraction. Deep Learning allows to implicitly capture intricate structures of large-scale data and ideally suited to some of the hardware architectures that are currently available.




Proceedings of the 3rd International Conference on Multimedia Technology (ICMT 2013)


Book Description

Proceedings of the 3rd International Conference on Multimedia Technology (ICMT2013) focuses on both the theory and applications of multimedia technology. The recent advances, new research findings and applications in the fields of theoretical, experimental and applied image & video processing and multimedia technology presented at the conference are brought together in this book. It will serve as a valuable reference for scientists and engineers working in multimedia and related fields. Prof. Aly A. Farag works at the University of Louisville, USA; Prof. Jian Yang works at Tsinghua University, China; Dr. Feng Jiao works at Nanjing University of Information Science & Technology, China.




Image and Video Technology


Book Description

This book constitutes the thoroughly refereed post-conference proceedings of five international workshops held in the framework of the 8th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2017, in Wuhan, China, in November 2017: Workshop on Human Behavior Analysis; Workshop on Educational Cloud and Image/Video Enriched Cloud Services, ECIVECS; Workshop: Vision Meets Graphics, VG; Workshop on Active Electro-Optical Sensors for Aerial and Space Imaging, EO4AS; and Workshop on Computer Vision and Modern Vehicles, CVMV. The 34 revised full papers and 2 posters presented were carefully selected from 103 submissions. The papers cover the full range of state-of-the-art research in image and video technology with topics ranging from well-established areas to novel current trends.




Digital Interaction and Machine Intelligence


Book Description

This book presents the Proceedings of MIDI’2020 – 8th Machine Intelligence and Digital Interaction Conference, December 9–10, 2020, Warsaw, Poland, held online. The rapid development of artificial intelligence (AI) and its growing applications in many fields, such as intelligent voice assistants, e-commerce (chatbots) or navigation, make end users increasingly exposed to such systems. In a world where technological solutions based on artificial intelligence are created by people for people, the final success or failure of a newly created product depends on the focus on human needs. Therefore, it is important to integrate so far independent scientific areas: broadly defined artificial intelligence and human–technology interaction. This book is intended for specialists in the above fields and attempts to integrate the perspectives of engineers and social scientists. The book is a source of inspiration as well as practical and theoretical knowledge for all readers interested in new trends in the field of user-centered AI solutions.




Super-Resolution Imaging


Book Description

With the exponential increase in computing power and broad proliferation of digital cameras, super-resolution imaging is poised to become the next "killer app." The growing interest in this technology has manifested itself in an explosion of literature on the subject. Super-Resolution Imaging consolidates key recent research contributions from eminent scholars and practitioners in this area and serves as a starting point for exploration into the state of the art in the field. It describes the latest in both theoretical and practical aspects of direct relevance to academia and industry, providing a base of understanding for future progress. Features downloadable tools to supplement material found in the book Recent advances in camera sensor technology have led to an increasingly larger number of pixels being crammed into ever-smaller spaces. This has resulted in an overall decline in the visual quality of recorded content, necessitating improvement of images through the use of post-processing. Providing a snapshot of the cutting edge in super-resolution imaging, this book focuses on methods and techniques to improve images and video beyond the capabilities of the sensors that acquired them. It covers: History and future directions of super-resolution imaging Locally adaptive processing methods versus globally optimal methods Modern techniques for motion estimation How to integrate robustness Bayesian statistical approaches Learning-based methods Applications in remote sensing and medicine Practical implementations and commercial products based on super-resolution The book concludes by concentrating on multidisciplinary applications of super-resolution for a variety of fields. It covers a wide range of super-resolution imaging implementation techniques, including variational, feature-based, multi-channel, learning-based, locally adaptive, and nonparametric methods. This versatile book can be used as the basis for short courses for engineers and scientists, or as part of graduate-level courses in image processing.




Deep Learning through Sparse and Low-Rank Modeling


Book Description

Deep Learning through Sparse Representation and Low-Rank Modeling bridges classical sparse and low rank models-those that emphasize problem-specific Interpretability-with recent deep network models that have enabled a larger learning capacity and better utilization of Big Data. It shows how the toolkit of deep learning is closely tied with the sparse/low rank methods and algorithms, providing a rich variety of theoretical and analytic tools to guide the design and interpretation of deep learning models. The development of the theory and models is supported by a wide variety of applications in computer vision, machine learning, signal processing, and data mining. This book will be highly useful for researchers, graduate students and practitioners working in the fields of computer vision, machine learning, signal processing, optimization and statistics.