This book constitutes the refereed post-conference proceedings of four workshops held at the 15th Asian Conference on Computer Vision, ACCV 2020, which was held in Kyoto, Japan, in November/ December 2020.*The 13 papers were carefully reviewed and selected from the following two workshops: Machine Learning and Computing for Visual Semantic Analysis (MLCSA) and Multi-Visual-Modality Human Activity Understanding (MMHAU). *The conference and workshops were held virtually.

This two-volume set constitutes the refereed proceedings of the Third International Conference on Recent Trends in Image Processing and Pattern Recognition (RTIP2R) 2020, held in Aurangabad, India, in January 2020.The 78 revised full papers presented were carefully reviewed and selected from 329 submissions. The papers are organized in topical sections in the two volumes. Part I: Computer vision and applications; Data science and machine learning; Document understanding and Recognition. Part II: Healthcare informatics and medical imaging; Image analysis and recognition; Signal processing and pattern recognition; Image and signal processing in Agriculture.

Attention .NET developers, here is your starting point for learning how to create and publish augmented reality (AR) apps for iOS devices. This book introduces and explores iOS augmented reality mobile app development specifically for .NET developers. The continued adoption and popularity of Xamarin, a tool that allows cross-platform mobile application development, opens up many app publishing opportunities to .NET developers that were never before possible, including AR development. You will use Xamarin to target Apple's augmented reality framework, ARKit, to develop augmented reality apps in the language you prefer-C#. Begin your journey with a foundational introduction to augmented reality, ARKit, Xamarin, and .NET. You will learn how this remarkable collaboration of technologies can produce fantastic experiences, many of them never before tried by .NET developers. From there you will dive into the fundamentals and then explore various topics and AR features. Throughout your learning, proof of concepts will be demonstrated to reinforce learning. After reading this book you will have the fundamentals you need, as well as an understanding of the overarching concepts that combine them. You will come away with an understanding of the wide range of augmented reality features available for developers, including the newest features included in the latest versions of ARKit. What You Will Learn Create rich commercial and personal augmented reality mobile apps Explore the latest capabilities of ARKit Extend and customize chapter examples for building your own amazing apps Graduate from traditional 2D UI app interfaces to immersive 3D AR interfaces Who This Book Is For Developers who want to learn how to use .NET and C# to create augmented reality apps for iOS devices. It is recommended that developers have some Xamarin experience and are aware of the cross-platform options available to .NET. A paid Apple developer account is not needed to experiment with the AR code samples on your devices.

This book constitutes revised selected papers of the 9th International Conference on Analysis of Images, Social Networks and Texts, AIST 2020, held in Moscow, Russia, in october 2020. Due to the COVID-19 pandemic the conference was held online. The 14 full papers, 9 short papers and 4 poster papers were carefully reviewed and selected from 108 qualified submissions. The papers are organized in topical sections on natural language processing; computer vision; social network analysis; data analysis and machine learning; theoretical machine learning and optimization; process mining; posters.

This book discusses human emotion recognition from face images using different modalities, highlighting key topics in facial expression recognition, such as the grid formation, distance signature, shape signature, texture signature, feature selection, classifier design, and the combination of signatures to improve emotion recognition. The book explains how six basic human emotions can be recognized in various face images of the same person, as well as those available from benchmark face image databases like CK+, JAFFE, MMI, and MUG. The authors present the concept of signatures for different characteristics such as distance and shape texture, and describe the use of associated stability indices as features, supplementing the feature set with statistical parameters such as range, skewedness, kurtosis, and entropy. In addition, they demonstrate that experiments with such feature choices offer impressive results, and that performance can be further improved by combining the signatures rather than using them individually. There is an increasing demand for emotion recognition in diverse fields, including psychotherapy, biomedicine, and security in government, public and private agencies. This book offers a valuable resource for researchers working in these areas.

This book constitutes the refereed proceedings of the 28th International Symposium on Graph Drawing and Network Visualization, GD 2020, which was held during September 16-18, 2020. The conference was planned to take place in Vancouver, Canada, but changed to an online format due to the COVID-19 pandemic. The 29 full and 9 short papers presented in this volume were carefully reviewed and selected from 82 submissions. They were organized in topical sections named: gradient descent and queue layouts; drawing tree-like graphs, visualization, and special drawings of elementary graphs; restricted drawings of special graph classes; orthogonality; topological constraints; crossings, k-planar graphs; planarity; graphs drawing contest.

This two-volume set constitutes the refereed proceedings of the Third International Conference on Recent Trends in Image Processing and Pattern Recognition (RTIP2R) 2020, held in Aurangabad, India, in January 2020.The 78 revised full papers presented were carefully reviewed and selected from 329 submissions. The papers are organized in topical sections in the two volumes. Part I: Computer vision and applications; Data science and machine learning; Document understanding and Recognition. Part II: Healthcare informatics and medical imaging; Image analysis and recognition; Signal processing and pattern recognition; Image and signal processing in Agriculture.

This book attempts to improve algorithms by novel theories and complex data analysis in different scopes including object detection, remote sensing, data transmission, data fusion, gesture recognition, and edical image processing and analysis. The book is directed to the Ph.D. students, professors, researchers, and software developers working in the areas of digital video processing and computer vision technologies.

The two-volume set LNCS 12615 + 12616 constitutes the refereed proceedings of the 12th International Conference on Intelligent Human Computer Interaction, IHCI 2020, which took place in Daegu, South Korea, during November 24-26, 2020.The 75 full and 18 short papers included in these proceedings were carefully reviewed and selected from a total of 185 submissions. The papers were organized in topical sections named: cognitive modeling and systems; biomedical signal processing and complex problem solving; natural language, speech, voice and study; algorithms and related applications; crowd sourcing and information analysis; intelligent usability and test system; assistive living; image processing and deep learning; and human-centered AI applications.

This book constitutes the refereed proceedings of the 32nd Australasian Database Conference, ADC 2021, held in Dunedin, New Zealand, in January/February 2021. The 17 full papers presented were carefully reviewed and selected from 21 submissions. The Australasian Database Conference is an annual international forum for sharing the latest research advancements and novel applications of database systems, data-driven applications, and data analytics between researchers and practitioners from around the globe, particularly Australia and New Zealand. ADC shares novel research solutions to problems of todays information society that fullfil the needs of heterogeneous applications and environments and to identify new issues and directions for future research and development work.

This two-volume set (CCIS 1367-1368) constitutes reviewed and selected papers from the 10th International Advanced Computing Conference, IACC 2020, held in December 2020. The 65 full papers and 2 short papers presented in two volumes were thorougly reviewed and selected from 286 submissions. The papers are organized in the following topical sections: Application of Artificial Intelligence and Machine Learning in Healthcare; Using Natural Language Processing for Solving Text and Language related Applications; Using Different Neural Network Architectures for Interesting applications; Using AI for Plant and Animal related Applications.- Applications of Blockchain and IoT.- Use of Data Science for Building Intelligence Applications; Innovations in Advanced Network Systems; Advanced Algorithms for Miscellaneous Domains; New Approaches in Software Engineering.

This book constitutes the refereed proceedings of the 6th International Symposium on Advances in Signal Processing and Intelligent Recognition Systems, SIRS 2020, held in Chennai, India, in October 2020. Due to the COVID-19 pandemic the conference was held online. The 22 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 50 submissions. The papers cover wide research fields including information retrieval, human-computer interaction (HCI), information extraction, speech recognition.

This book constitutes the refereed proceedings of the 14th International Symposium on Perception, Representations, Image, Sound, Music, CMMR 2019, held in Marseille, France, in October 2019. The 46 full papers presented were selected from 105 submissions. The papers are grouped in 9 sections. The first three sections are related to music information retrieval, computational musicology and composition tools, followed by a section on notations and instruments distributed on mobile devices. The fifth section concerns auditory perception and cognition, while the three following sections are related to sound design and sonic and musical interactions. The last section contains contributions that relate to Jean-Claude Risset's research.

This book provides a detailed survey of the methods that were recently developed to handle advanced versions of the blind source separation problem, which involve several types of nonlinear mixtures. Another attractive feature of the book is that it is based on a coherent framework. More precisely, the authors first present a general procedure for developing blind source separation methods. Then, all reported methods are defined with respect to this procedure. This allows the reader not only to more easily follow the description of each method but also to see how these methods relate to one another. The coherence of this book also results from the fact that the same notations are used throughout the chapters for the quantities (source signals and so on) that are used in various methods. Finally, among the quite varied types of processing methods that are presented in this book, a significant part of this description is dedicated to methods based on artificial neural networks, especially recurrent ones, which are currently of high interest to the data analysis and machine learning community in general, beyond the more specific signal processing and blind source separation communities.

The 6-volume set, comprising the LNCS books 12535 until 12540, constitutes the refereed proceedings of 28 out of the 45 workshops held at the 16th European Conference on Computer Vision, ECCV 2020. The conference was planned to take place in Glasgow, UK, during August 23-28, 2020, but changed to a virtual format due to the COVID-19 pandemic. The 249 full papers, 18 short papers, and 21 further contributions included in the workshop proceedings were carefully reviewed and selected from a total of 467 submissions. The papers deal with diverse computer vision topics. Part III includes the Advances in Image Manipulation Workshop and Challenges.

This book comprises select peer-reviewed proceedings of the medical challenge - C-NMC challenge: Classification of normal versus malignant cells in B-ALL white blood cancer microscopic images. The challenge was run as part of the IEEE International Symposium on Biomedical Imaging (IEEE ISBI) 2019 held at Venice, Italy in April 2019. Cell classification via image processing has recently gained interest from the point of view of building computer-assisted diagnostic tools for blood disorders such as leukaemia. In order to arrive at a conclusive decision on disease diagnosis and degree of progression, it is very important to identify malignant cells with high accuracy. Computer-assisted tools can be very helpful in automating the process of cell segmentation and identification because morphologically both cell types appear similar. This particular challenge was run on a curated data set of more than 14000 cell images of very high quality. More than 200 international teams participated in the challenge. This book covers various solutions using machine learning and deep learning approaches. The book will prove useful for academics, researchers, and professionals interested in building low-cost automated diagnostic tools for cancer diagnosis and treatment.

This 8-volumes set constitutes the refereed of the 25th International Conference on Pattern Recognition Workshops, ICPR 2020, held virtually in Milan, Italy and rescheduled to January 10 - 11, 2021 due to Covid-19 pandemic. The 416 full papers presented in these 8 volumes were carefully reviewed and selected from about 700 submissions. The 46 workshops cover a wide range of areas including machine learning, pattern analysis, healthcare, human behavior, environment, surveillance, forensics and biometrics, robotics and egovision, cultural heritage and document analysis, retrieval, and women at ICPR2020.

The two-volume set LNCS 12572 and 1273 constitutes the thoroughly refereed proceedings of the 27th International Conference on MultiMedia Modeling, MMM 2021, held in Prague, Czech Republic, in June2021. Of the 211 submitted regular papers, 40 papers were selected for oral presentation and 33 for poster presentation; 16 special session papers were accepted as well as 2 papers for a demo presentation and 17 papers for participation at the Video Browser Showdown 2021. The papers cover topics such as: multimedia indexing; multimedia mining; multimedia abstraction and summarization; multimedia annotation, tagging and recommendation; multimodal analysis for retrieval applications; semantic analysis of multimedia and contextual data; multimedia fusion methods; multimedia hyperlinking; media content browsing and retrieval tools; media representation and algorithms; audio, image, video processing, coding and compression; multimedia sensors and interaction modes; multimedia privacy, security and content protection; multimedia standards and related issues; advances in multimedia networking and streaming; multimedia databases, content delivery and transport; wireless and mobile multimedia networking; multi-camera and multi-view systems; augmented and virtual reality, virtual environments; real-time and interactive multimedia applications; mobile multimedia applications; multimedia web applications; multimedia authoring and personalization; interactive multimedia and interfaces; sensor networks; social and educational multimedia applications; and emerging trends.

This book contains the invited and contributed papers selected for presentation at SOFSEM 2021, the 47th International Conference on Current Trends in Theory and Practice of Computer Science, which was held online during January 25-28, 2021, hosted by the Free University of Bozen-Bolzano, Italy.The 33 full and 7 short papers included in the volume were carefully reviewed and selected from 100 submissions. They were organized in topical sections on: foundations of computer science; foundations of software engineering; foundations of data science and engineering; and foundations of algorithmic computational biology. The book also contains 5 invited papers.

The two-volume set LNCS 12572 and 1273 constitutes the thoroughly refereed proceedings of the 27th International Conference on MultiMedia Modeling, MMM 2021, held in Prague, Czech Republic, in June2021. Of the 211 submitted regular papers, 40 papers were selected for oral presentation and 33 for poster presentation; 16 special session papers were accepted as well as 2 papers for a demo presentation and 17 papers for participation at the Video Browser Showdown 2021. The papers cover topics such as: multimedia indexing; multimedia mining; multimedia abstraction and summarization; multimedia annotation, tagging and recommendation; multimodal analysis for retrieval applications; semantic analysis of multimedia and contextual data; multimedia fusion methods; multimedia hyperlinking; media content browsing and retrieval tools; media representation and algorithms; audio, image, video processing, coding and compression; multimedia sensors and interaction modes; multimedia privacy, security and content protection; multimedia standards and related issues; advances in multimedia networking and streaming; multimedia databases, content delivery and transport; wireless and mobile multimedia networking; multi-camera and multi-view systems; augmented and virtual reality, virtual environments; real-time and interactive multimedia applications; mobile multimedia applications; multimedia web applications; multimedia authoring and personalization; interactive multimedia and interfaces; sensor networks; social and educational multimedia applications; and emerging trends.

This book constitutes the First 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2020, which was held in conjunction with the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020. The challenge took place virtually due to the COVID-19 pandemic.The 2 full and 8 short papers presented together with an overview paper in this volume were carefully reviewed and selected form numerous submissions. This challenge aims to evaluate and compare the current state-of-the-art methods for automatic head and neck tumor segmentation. In the context of this challenge, a dataset of 204 delineated PET/CT images was made available for training as well as 53 PET/CT images for testing. Various deep learning methods were developed by the participants with excellent results.

This book constitutes the thoroughly refereed proceedings of the themed workshops of the 6th International Conference on Life System Modeling and Simulation, LSMS 2020, and of the 6th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2020, held in Hangzhou, China, in October 2020.The 36 full and 2 short papers presented were carefully reviewed and selected from over 165 submissions. The papers of this volume are organized in topical sections on: smart energy systems and devices; intelligent manufacturing and systems; and intelligent biology and information systems.

Organizations spend huge resources in developing software that can perform the way a human does. Image classification, object detection and tracking, pose estimation, facial recognition, and sentiment estimation all play a major role in solving computer vision problems. This book will bring into focus these and other deep learning architectures and techniques to help you create solutions using Keras and the TensorFlow library. You'll also review mutliple neural network architectures, including LeNet, AlexNet, VGG, Inception, R-CNN, Fast R-CNN, Faster R-CNN, Mask R-CNN, YOLO, and SqueezeNet and see how they work alongside Python code via best practices, tips, tricks, shortcuts, and pitfalls. All code snippets will be broken down and discussed thoroughly so you can implement the same principles in your respective environments. Computer Vision Using Deep Learning offers a comprehensive yet succinct guide that stitches DL and CV together to automate operations, reduce human intervention, increase capability, and cut the costs. What You'll Learn Examine deep learning code and concepts to apply guiding principals to your own projects Classify and evaluate various architectures to better understand your options in various use cases Go behind the scenes of basic deep learning functions to find out how they work Who This Book Is For Professional practitioners working in the fields of software engineering and data science. A working knowledge of Python is strongly recommended. Students and innovators working on advanced degrees in areas related to computer vision and Deep Learning.

This book constitutes the refereed proceedings of the 8th Language and Technology Conference: Challenges for Computer Science and Linguistics, LTC 2017, held in Poznan, Poland, in November 2017. The 26 revised papers presented in this volume were carefully reviewed and selected from 97 submissions. The papers selected to this volume belong to various fields of: Language Resources, Tools and Evaluation, Less-Resourced-Languages, Speech Processing, Morphology, Computational Semantics, Machine Translation, and Information Retrieval and Information Extraction.

This book constitutes the refereed proceedings of the 11th International Conference on Decision and Game Theory for Security, GameSec 2020,held in College Park, MD, USA, in October 2020. Due to COVID-19 pandemic the conference was held virtually The 21 full papers presented together with 2 short papers were carefully reviewed and selected from 29 submissions. The papers focus on machine learning and security; cyber deception; cyber-physical systems security; security of network systems; theoretic foundations of security games; emerging topics.