Visual Saliency From Pixel Level To Object Level Analysis
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| Author | : Jianming Zhang |
| Publisher | : Springer |
| Total Pages | : 138 |
| Release | : 2019-01-21 |
| Genre | : Computers |
| ISBN | : 3030048314 |
This book provides an introduction to recent advances in theory, algorithms and application of Boolean map distance for image processing. Applications include modeling what humans find salient or prominent in an image, and then using this for guiding smart image cropping, selective image filtering, image segmentation, image matting, etc. In this book, the authors present methods for both traditional and emerging saliency computation tasks, ranging from classical low-level tasks like pixel-level saliency detection to object-level tasks such as subitizing and salient object detection. For low-level tasks, the authors focus on pixel-level image processing approaches based on efficient distance transform. For object-level tasks, the authors propose data-driven methods using deep convolutional neural networks. The book includes both empirical and theoretical studies, together with implementation details of the proposed methods. Below are the key features for different types of readers. For computer vision and image processing practitioners: Efficient algorithms based on image distance transforms for two pixel-level saliency tasks; Promising deep learning techniques for two novel object-level saliency tasks; Deep neural network model pre-training with synthetic data; Thorough deep model analysis including useful visualization techniques and generalization tests; Fully reproducible with code, models and datasets available. For researchers interested in the intersection between digital topological theories and computer vision problems: Summary of theoretic findings and analysis of Boolean map distance; Theoretic algorithmic analysis; Applications in salient object detection and eye fixation prediction. Students majoring in image processing, machine learning and computer vision: This book provides up-to-date supplementary reading material for course topics like connectivity based image processing, deep learning for image processing; Some easy-to-implement algorithms for course projects with data provided (as links in the book); Hands-on programming exercises in digital topology and deep learning.
| Author | : IUPsyS |
| Publisher | : John Wiley & Sons |
| Total Pages | : 496 |
| Release | : 2018-11-05 |
| Genre | : Psychology |
| ISBN | : 1119362075 |
Highlights from one of the most successful international psychology conferences since the beginning of this century Diversity in Harmony distills the Proceedings of the 31st International Congress of Psychology into selected readings that highlight the Congress’s theme. The text includes research that offers recent insights gained from multidisciplinary perspectives and methodologies. The volume also contains chapters that put psychology at the center of our understanding and ability to address the many problems facing groups and individuals in modern society. As the contributors clearly show, the social problems often require multidisciplinary approaches. With contributions from experts from around the globe, the book explores a wealth of topics that examine new synergies such as artificial empathy, prosocial primates and understanding about others’ actions in chimpanzees and humans. The volume also contains readings on psychology confronting societal challenges with topics including: Culturally relevant personality assessment; Emotion-related self-regulation and Children's social, psychological and academic functioning. This vital resource: Presents readings from presentations that were highlighted at the 31st International Congress of Psychology Includes contributions from an international panel of renowned experts Offers information that compares the minds of primates and contemporary humans, and examines human cognitive capability Contains 24 chapters that explore a wide range of topics presented at the Congress Written for professionals and students in the field, Diversity in Harmony is filled with contributions from noted experts and offers a reflection of the state of psychology in the second decade of the 21st century.
| Author | : Sebastiano Battiato |
| Publisher | : Springer |
| Total Pages | : 814 |
| Release | : 2017-10-13 |
| Genre | : Computers |
| ISBN | : 3319685481 |
The two-volume set LNCS 10484 and 10485 constitutes the refereed proceedings of the 19th International Conference on Image Analysis and Processing, ICIAP 2017, held in Catania, Italy, in September 2017. The 138 papers presented were carefully reviewed and selected from 229 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; multiview geometry and 3D computer vision; image analysis, detection and recognition; multimedia; biomedical and assistive technology; information forensics and security; imaging for cultural heritage and archaeology; and imaging solutions for improving the quality of life.
| Author | : Yu-Jin Zhang |
| Publisher | : CRC Press |
| Total Pages | : 363 |
| Release | : 2022-10-05 |
| Genre | : Computers |
| ISBN | : 1000689425 |
This book focuses on seven commonly used image analysis techniques. It covers aspects from basic principles and practical methods, to new advancement of each selected technique to help readers solve image‐processing related problems in real-life situations. The selected techniques include image segmentation, segmentation evaluation and comparison, saliency object detection, motion analysis, mathematical morphology methods, face recognition and expression classification. The author offers readers a three‐step strategy toward problem‐solving: first, essential principles; then, a detailed explanation; and finally, a discussion on practical and working techniques for specific tasks. He also encourages readers to make full use of available materials from the latest developments and trends. This is an excellent book for those who do not have a complete foundation in image technology but need to use image analysis techniques to perform specific tasks in particular applications.
| Author | : Slimane Hammoudi |
| Publisher | : Springer Nature |
| Total Pages | : 168 |
| Release | : 2020-07-29 |
| Genre | : Computers |
| ISBN | : 3030545954 |
This book constitutes the thoroughly refereed proceedings of the 8th International Conference on Data Management Technologies and Applications, DATA 2019, held in Prague, Czech Republic, in July 2019. The 8 revised full papers were carefully reviewed and selected from 90 submissions. The papers deal with the following topics: decision support systems, data analytics, data and information quality, digital rights management, big data, knowledge management, ontology engineering, digital libraries, mobile databases, object-oriented database systems, and data integrity.
| Author | : Gian Luca Foresti |
| Publisher | : Springer Nature |
| Total Pages | : 588 |
| Release | : 2023-09-04 |
| Genre | : Computers |
| ISBN | : 3031431480 |
This two-volume set LNCS 14233-14234 constitutes the refereed proceedings of the 22nd International Conference on Image Analysis and Processing, ICIAP 2023, held in Udine, Italy, during September 11–15, 2023. The 85 full papers presented together with 7 short papers were carefully reviewed and selected from 144 submissions. The conference focuses on video analysis and understanding; pattern recognition and machine learning; deep learning; multi-view geometry and 3D computer vision; image analysis, detection and recognition; multimedia; biomedical and assistive technology; digital forensics and biometrics; image processing for cultural heritage; and robot vision.
| Author | : Jianwei Zhang |
| Publisher | : Frontiers Media SA |
| Total Pages | : 295 |
| Release | : 2023-02-02 |
| Genre | : Science |
| ISBN | : 2889762548 |
The purpose of this Research Topic is to reflect and discuss links between neuroscience, psychology, computer science and robotics with regards to the topic of cross-modal learning which has, in recent years, emerged as a new area of interdisciplinary research. The term cross-modal learning refers to the synergistic synthesis of information from multiple sensory modalities such that the learning that occurs within any individual sensory modality can be enhanced with information from one or more other modalities. Cross-modal learning is a crucial component of adaptive behavior in a continuously changing world, and examples are ubiquitous, such as: learning to grasp and manipulate objects; learning to walk; learning to read and write; learning to understand language and its referents; etc. In all these examples, visual, auditory, somatosensory or other modalities have to be integrated, and learning must be cross-modal. In fact, the broad range of acquired human skills are cross-modal, and many of the most advanced human capabilities, such as those involved in social cognition, require learning from the richest combinations of cross-modal information. In contrast, even the very best systems in Artificial Intelligence (AI) and robotics have taken only tiny steps in this direction. Building a system that composes a global perspective from multiple distinct sources, types of data, and sensory modalities is a grand challenge of AI, yet it is specific enough that it can be studied quite rigorously and in such detail that the prospect for deep insights into these mechanisms is quite plausible in the near term. Cross-modal learning is a broad, interdisciplinary topic that has not yet coalesced into a single, unified field. Instead, there are many separate fields, each tackling the concerns of cross-modal learning from its own perspective, with currently little overlap. We anticipate an accelerating trend towards integration of these areas and we intend to contribute to that integration. By focusing on cross-modal learning, the proposed Research Topic can bring together recent progress in artificial intelligence, robotics, psychology and neuroscience.
| Author | : Guoping Qiu |
| Publisher | : Springer |
| Total Pages | : 780 |
| Release | : 2010-09-13 |
| Genre | : Computers |
| ISBN | : 3642156967 |
The 2010 Pacific-Rim Conference on Multimedia (PCM 2010) was held in Shanghai at Fudan University, during September 21–24, 2010. Since its inauguration in 2000, PCM has been held in various places around the Pacific Rim, namely Sydney (PCM 2000), Beijing (PCM 2001), Hsinchu (PCM 2002), Singapore (PCM 2003), Tokyo (PCM 2004), Jeju (PCM 2005), Zhejiang (PCM 2006), Hong Kong (PCM 2007), Tainan (PCM 2008), and Bangkok (PCM 2009). PCM is a major annual international conference organized as a forum for the dissemination of state-of-the-art technological advances and research results in the fields of theoretical, experimental, and applied multimedia analysis and processing. PCM 2010 featured a comprehensive technical program which included 75 oral and 56 poster presentations selected from 261 submissions from Australia, Canada, China, France, Germany, Hong Kong, India, Iran, Italy, Japan, Korea, Myanmar, Norway, Singapore, Taiwan, Thailand, the UK, and the USA. Three distinguished researchers, Prof. Zhi-Hua Zhou from Nanjing University, Dr. Yong Rui from Microsoft, and Dr. Tie-Yan Liu from Microsoft Research Asia delivered three keynote talks to the conference. We are very grateful to the many people who helped to make this conference a s- cess. We would like to especially thank Hong Lu for local organization, Qi Zhang for handling the publication of the proceedings, and Cheng Jin for looking after the c- ference website and publicity. We thank Fei Wu for organizing the special session on large-scale multimedia search in the social network settings.
| Author | : S. Kevin Zhou |
| Publisher | : Academic Press |
| Total Pages | : 460 |
| Release | : 2017-01-18 |
| Genre | : Computers |
| ISBN | : 0128104090 |
Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Covers common research problems in medical image analysis and their challenges Describes deep learning methods and the theories behind approaches for medical image analysis Teaches how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Includes a Foreword written by Nicholas Ayache
| Author | : Cheng-Lin Liu |
| Publisher | : Springer |
| Total Pages | : 379 |
| Release | : 2016-11-11 |
| Genre | : Computers |
| ISBN | : 3319496859 |
This book constitutes the refereed proceedings of the 8th International Conference on Brain Inspired Cognitive Systems, BICS 2016, held in Beijing, China, in November 2016. The 32 full papers presented were carefully reviewed and selected from 43 submissions. They discuss the emerging areas and challenges, present the state of the art of brain-inspired cognitive systems research and applications in diverse fields by covering many topics in brain inspired cognitive systems related research including biologically inspired systems, cognitive neuroscience, models consciousness, and neural computation.
