This book provides an in-depth investigation on the psychological phenomenon "reactance" in the context of Human-Computer Interaction (HCI). The author argues that the complexity and autonomy of modern technology can sometimes be overwhelming and can then be perceived as a threat to freedom by its users, thereby diminishing acceptance. The book investigates if and how this is the case and provides strategies to regain the lost acceptance. Topics include relevance of reactance on HCI, triggers for reactance, consequences of reactance, measurement of reactance, and countermeasures to reactance.

Machine Learning and Visual Perception provides an up-to-date overview on the topic, including the PAC model, decision tree, Bayesian learning, support vector machines, AdaBoost, compressive sensing and so on.Both classic and novel algorithms are introduced in classifier design, face recognition, deep learning, time series recognition, image classification, and object detection.

This book focuses on enabling mobile robots to recognize scenes in indoor environments, in order to allow them to determine which actions are appropriate at which points in time. In concrete terms, future robots will have to solve the classification problem represented by scene recognition sufficiently well for them to act independently in human-centered environments. To achieve accurate yet versatile indoor scene recognition, the book presents a hierarchical data structure for scenes - the Implicit Shape Model trees. Further, it also provides training and recognition algorithms for these trees. In general, entire indoor scenes cannot be perceived from a single point of view. To address this problem the authors introduce Active Scene Recognition (ASR), a concept that embeds canonical scene recognition in a decision-making system that selects camera views for a mobile robot to drive to so that it can find objects not yet localized. The authors formalize the automatic selection of camera views as a Next-Best-View (NBV) problem to which they contribute an algorithmic solution, which focuses on realistic problem modeling while maintaining its computational efficiency. Lastly, the book introduces a method for predicting the poses of objects to be searched, establishing the otherwise missing link between scene recognition and NBV estimation.

This book constitutes the proceedings of the 15th IFIP International Conference on Network and Parallel Computing, NPC 2018, held in Muroran, Japan, in November/December 2018. The 22 full and 12 short papers presented in this volume were carefully reviewed and selected from 72 submissions. The papers cover traditional areas of network and parallel computing, including parallel applications, distributed algorithms, parallel architectures, software environments, and distributed tools.

This book addresses Assistive Augmentation, highlighting the design and development of assistive technologies, user interfaces, and interactions that seamlessly integrate with a user's mind, body, and behavior, providing an enhanced perception. Our senses are the dominant channel we use to perceive the world around us. Whether they have impairments or not, people often find themselves at the limits of their sensorial capabilities. Some seek assistive or enhancing devices that enable them to carry out specific tasks or even transform them into a "superhuman" with capabilities well beyond the ordinary. The overarching topic of this book revolves around the design and development of technologies and interfaces that provide enhanced physical, sensorial and cognitive capabilities: "Assistive Augmentation". The Assistive Augmentation community convened at an interdisciplinary workshop at the 2014 International Conference on Human Factors in Computing Systems (CHI) in Toronto, Canada. The community is comprised of researchers and practitioners who work at the junction of human-computer interaction, assistive technology and human augmentation. This edited volume, which represents the first tangible outcome of the workshop, presents stimulating discussions on the challenges of Assistive Augmentation as examined through case studies. These studies focus on two main areas: (1) Augmented Sensors and Feedback Modalities, and (2) Design for Assistive Augmentation.

This book constitutes the proceedings of the 7th International Workshop on Computational Topology in Image Context, CTIC 2019, held in Malaga, Spain, in January 2019. The 14 papers presented in this volume were carefully reviewed and selected from 21 submissions. Papers deal with theoretical issues but most of them put the attention on the applicability of concepts and algorithms. These were designed to deal with objects and images, but also with the speech signal. The final application must be for instance in the medical domain or in the robotics one.

This book, compiles, presents, and explains the most important meta-heuristic and evolutionary optimization algorithms whose successful performance has been proven in different fields of engineering, and it includes application of these algorithms to important engineering optimization problems. In addition, this book guides readers to studies that have implemented these algorithms by providing a literature review on developments and applications of each algorithm. This book is intended for students, but can be used by researchers and professionals in the area of engineering optimization.

The book includes extended versions of selected papers discussed and presented at the 5th International Doctoral Symposium on Applied Computation and Security Systems (ACSS 2018) held in Kolkata, India on February 9-11, 2018. The symposium was organized by the University of Calcutta's Department of Computer Science & Engineering and A. K. Choudhury School of Information Technology, and the International partners were Ca Foscari University of Venice, Italy and Bialystok University of Technology, Poland. Reflect the symposium's sessions, the book discusses topics such as biometrics, image processing, pattern recognition, algorithms, cloud computing, wireless sensor networks and security systems.

This book shows how mathematics, computer science and science can be usefully and seamlessly intertwined. It begins with a general model of cognitive processes in a network of computational nodes, such as neurons, using a variety of tools from mathematics, computational science and neurobiology. It then moves on to solve the diffusion model from a low-level random walk point of view. It also demonstrates how this idea can be used in a new approach to solving the cable equation, in order to better understand the neural computation approximations. It introduces specialized data for emotional content, which allows a brain model to be built using MatLab tools, and also highlights a simple model of cognitive dysfunction.

This book highlights the methods and applications for roadside video data analysis, with a particular focus on the use of deep learning to solve roadside video data segmentation and classification problems. It describes system architectures and methodologies that are specifically built upon learning concepts for roadside video data processing, and offers a detailed analysis of the segmentation, feature extraction and classification processes. Lastly, it demonstrates the applications of roadside video data analysis including scene labelling, roadside vegetation classification and vegetation biomass estimation in fire risk assessment.

This book provides a self-study program on how mathematics, computer science and science can be usefully and seamlessly intertwined. Learning to use ideas from mathematics and computation is essential for understanding approaches to cognitive and biological science. As such the book covers calculus on one variable and two variables and works through a number of interesting first-order ODE models. It clearly uses MatLab in computational exercises where the models cannot be solved by hand, and also helps readers to understand that approximations cause errors - a fact that must always be kept in mind.

This book constitutes the proceedings of the Workshop on Shape in Medical Imaging, ShapeMI 2018, held in conjunction with the 21st International Conference on Medical Image Computing, MICCAI 2018, in Granada, Spain, in September 2018. The 26 full papers and 2 short papers presented were carefully reviewed and selected for inclusion in this volume. The papers discuss novel approaches and applications in shape and geometry processing and their use in research and clinical studies and explore novel, cutting-edge theoretical methods and their usefulness for medical applications, e.g., from the fields of geometric learning or spectral shape analysis.

This book constitutes the refereed post-conference proceedings of the 8th International Conference on Big Data Technologies and Applications, BDTA 2017, held in Gwangju, South Korea, in November 2017. The 15 revised full papers were carefully reviewed and selected from 25 submissions and handle theoretical foundations and practical applications which premise the new generation of data analytics and engineering. The contributions deal with following topics: privacy and security, image processing, context awareness, s/w engineering and e-commerce, social media and health care.

This book gathers outstanding research papers presented at the International Conference on Intelligent Vision and Computing (ICIVC 2021), held online during October 03-04, 2021. ICIVC 2021 is organised by Sur University, Oman. The book presents novel contributions in intelligent vision and computing and serves as reference material for beginners and advanced research. The topics covered are intelligent systems, intelligent data analytics and computing, intelligent vision and applications collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal natural language processing.

The four-volume set LNCS 11256, 11257, 11258, and 11259 constitutes the refereed proceedings of the First Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2018, held in Guangzhou, China, in November 2018. The 179 revised full papers presented were carefully reviewed and selected from 399 submissions. The papers have been organized in the following topical sections: Part I: Biometrics, Computer Vision Application. Part II: Deep Learning. Part III: Document Analysis, Face Recognition and Analysis, Feature Extraction and Selection, Machine Learning. Part IV: Object Detection and Tracking, Performance Evaluation and Database, Remote Sensing.

The four-volume set LNCS 11256, 11257, 11258, and 11259 constitutes the refereed proceedings of the First Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2018, held in Guangzhou, China, in November 2018. The 179 revised full papers presented were carefully reviewed and selected from 399 submissions. The papers have been organized in the following topical sections: Part I: Biometrics, Computer Vision Application. Part II: Deep Learning. Part III: Document Analysis, Face Recognition and Analysis, Feature Extraction and Selection, Machine Learning. Part IV: Object Detection and Tracking, Performance Evaluation and Database, Remote Sensing.

This book shows cognitive scientists in training how mathematics, computer science and science can be usefully and seamlessly intertwined. It is a follow-up to the first two volumes on mathematics for cognitive scientists, and includes the mathematics and computational tools needed to understand how to compute the terms in the Fourier series expansions that solve the cable equation. The latter is derived from first principles by going back to cellular biology and the relevant biophysics. A detailed discussion of ion movement through cellular membranes, and an explanation of how the equations that govern such ion movement leading to the standard transient cable equation are included. There are also solutions for the cable model using separation of variables, as well an explanation of why Fourier series converge and a description of the implementation of MatLab tools to compute the solutions. Finally, the standard Hodgkin - Huxley model is developed for an excitable neuron and is solved using MatLab.

This book offers a self-study program on how mathematics, computer science and science can be profitably and seamlessly intertwined. This book focuses on two variable ODE models, both linear and nonlinear, and highlights theoretical and computational tools using MATLAB to explain their solutions. It also shows how to solve cable models using separation of variables and the Fourier Series.

This book constitutes the refereed joint proceedings of the First International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2018, the First International Workshop on Deep Learning Fails, DLF 2018, and the First International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 4 full MLCN papers, the 6 full DLF papers, and the 6 full iMIMIC papers included in this volume were carefully reviewed and selected. The MLCN contributions develop state-of-the-art machine learning methods such as spatio-temporal Gaussian process analysis, stochastic variational inference, and deep learning for applications in Alzheimer's disease diagnosis and multi-site neuroimaging data analysis; the DLF papers evaluate the strengths and weaknesses of DL and identify the main challenges in the current state of the art and future directions; the iMIMIC papers cover a large range of topics in the field of interpretability of machine learning in the context of medical image analysis.

This book constitutes the refereed conference proceedings of the 12th International Conference on Multi-disciplinary Trends in Artificial Intelligence, MIWAI 2018, held in Hanoi, Vietnam, in November 2018. The 16 full papers presented together with 9 short papers were carefully reviewed and selected from 65 submissions. They are organized in the following topical sections: control, planning and scheduling, pattern recognition, knowledge mining, software applications, strategy games and others.

The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.

The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.

The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.

The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.

The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.