Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download VipIMAGE 2019 PDF full book. Access full book title VipIMAGE 2019 by João Manuel R. S. Tavares. Download full books in PDF and EPUB format.
Author: João Manuel R. S. Tavares Publisher: Springer Nature ISBN: 3030320405 Category : Medical Languages : en Pages : 706
Book Description
This book gathers full papers presented at the VipIMAGE 2019—VII ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing—held on October 16-18, 2019, in Porto, Portugal. It discusses cutting-edge methods, findings, and applications related to 3D vision, bio- and medical imaging, computer-aided diagnosis, image enhancement, image processing and analysis, virtual reality, and also describes in detail advanced image analysis techniques, such as image segmentation and feature selection, as well as statistical and geometrical modeling. The book provides both researchers and professionals with extensive and timely insights into advanced imaging techniques for various application purposes.
Author: João Manuel R. S. Tavares Publisher: Springer Nature ISBN: 3030320405 Category : Medical Languages : en Pages : 706
Book Description
This book gathers full papers presented at the VipIMAGE 2019—VII ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing—held on October 16-18, 2019, in Porto, Portugal. It discusses cutting-edge methods, findings, and applications related to 3D vision, bio- and medical imaging, computer-aided diagnosis, image enhancement, image processing and analysis, virtual reality, and also describes in detail advanced image analysis techniques, such as image segmentation and feature selection, as well as statistical and geometrical modeling. The book provides both researchers and professionals with extensive and timely insights into advanced imaging techniques for various application purposes.
Author: Eva Irene Brooks Publisher: Springer Nature ISBN: 3030784487 Category : Technology & Engineering Languages : en Pages : 215
Book Description
This book constitutes the refereed post-conference proceedings the 5th EAI International Conference on DLI 2020, Design, Leaning and Innovation, which took place in December 2020. Due to COVID-19 pandemic the conference was held virtually. The 14 revised full papers presented were carefully selected from 40 submissions and are organized in four thematic sessions on: digital technologies and learning; designing for innovation; digital games, gamification and robots; designs for innovative learning.
Author: João Manuel R. S. Tavares Publisher: Springer Nature ISBN: 3031100158 Category : Technology & Engineering Languages : en Pages : 304
Book Description
This book gathers selected, extended and revised contributions to the 17th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering and the 5th Conference on Imaging and Visualization (CMBBE 2021), held online on September 7-9, 2021, from Bonn, Germany. It reports on cutting-edge models, algorithms and imaging techniques for studying cells, tissues and organs in normal and pathological conditions. It covers numerical and machine learning methods, finite element modeling and virtual reality techniques, applied to understand biomechanics of movement, fluid and soft tissue biomechanics. It also reports on related advances in rehabilitation, surgery and diagnosis. All in all, this book offers a timely snapshot of the latest research and current challenges at the interface between biomedical engineering, computational biomechanics and biological imaging. Thus, it is expected to provide a source of inspiration for future research and cross-disciplinary collaborations.
Author: Jyotismita Chaki Publisher: Academic Press ISBN: 0323983952 Category : Science Languages : en Pages : 260
Book Description
Brain Tumor MRI Image Segmentation Using Deep Learning Techniques offers a description of deep learning approaches used for the segmentation of brain tumors. The book demonstrates core concepts of deep learning algorithms by using diagrams, data tables and examples to illustrate brain tumor segmentation. After introducing basic concepts of deep learning-based brain tumor segmentation, sections cover techniques for modeling, segmentation and properties. A focus is placed on the application of different types of convolutional neural networks, like single path, multi path, fully convolutional network, cascade convolutional neural networks, Long Short-Term Memory - Recurrent Neural Network and Gated Recurrent Units, and more. The book also highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in brain tumor segmentation. Provides readers with an understanding of deep learning-based approaches in the field of brain tumor segmentation, including preprocessing techniques Integrates recent advancements in the field, including the transformation of low-resolution brain tumor images into super-resolution images using deep learning-based methods, single path Convolutional Neural Network based brain tumor segmentation, and much more Includes coverage of Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN), Gated Recurrent Units (GRU) based Recurrent Neural Network (RNN), Generative Adversarial Networks (GAN), Auto Encoder based brain tumor segmentation, and Ensemble deep learning Model based brain tumor segmentation Covers research Issues and the future of deep learning-based brain tumor segmentation
Author: Hitoshi Iba Publisher: Springer Nature ISBN: 9811536856 Category : Computers Languages : en Pages : 437
Book Description
This book delivers the state of the art in deep learning (DL) methods hybridized with evolutionary computation (EC). Over the last decade, DL has dramatically reformed many domains: computer vision, speech recognition, healthcare, and automatic game playing, to mention only a few. All DL models, using different architectures and algorithms, utilize multiple processing layers for extracting a hierarchy of abstractions of data. Their remarkable successes notwithstanding, these powerful models are facing many challenges, and this book presents the collaborative efforts by researchers in EC to solve some of the problems in DL. EC comprises optimization techniques that are useful when problems are complex or poorly understood, or insufficient information about the problem domain is available. This family of algorithms has proven effective in solving problems with challenging characteristics such as non-convexity, non-linearity, noise, and irregularity, which dampen the performance of most classic optimization schemes. Furthermore, EC has been extensively and successfully applied in artificial neural network (ANN) research —from parameter estimation to structure optimization. Consequently, EC researchers are enthusiastic about applying their arsenal for the design and optimization of deep neural networks (DNN). This book brings together the recent progress in DL research where the focus is particularly on three sub-domains that integrate EC with DL: (1) EC for hyper-parameter optimization in DNN; (2) EC for DNN architecture design; and (3) Deep neuroevolution. The book also presents interesting applications of DL with EC in real-world problems, e.g., malware classification and object detection. Additionally, it covers recent applications of EC in DL, e.g. generative adversarial networks (GAN) training and adversarial attacks. The book aims to prompt and facilitate the research in DL with EC both in theory and in practice.
Author: Sebastia Massanet Publisher: Springer Nature ISBN: 303139965X Category : Computers Languages : en Pages : 755
Book Description
This book constitutes the proceedings of the 13th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2023, and 12th International Summer School on Aggregation Operators, AGOP 2023, jointly held in Palma de Mallorca, Spain, during September 4–8, 2023. The 71 full papers presented in this book were carefully reviewed and selected from 161 submissions. The papers are divided into special sessions on: Interval uncertainty; information fusion techniques based on aggregation functions, preaggregation functions and their generalizations; evaluative linguistic expressions, generalized quantifiers and applications; neural networks under uncertainty and imperfect information; imprecision modeling and management in XAI systems; recent trends in mathematical fuzzy logics; fuzzy graph-based models: theory and application; new frontiers of computational intelligence for pervasive healthcare systems; fuzzy implication functions; and new challenges and ideas in statistical inference and data analysis.
Author: Valeria V. Krzhizhanovskaya Publisher: Springer Nature ISBN: 3030504174 Category : Computers Languages : en Pages : 715
Book Description
The seven-volume set LNCS 12137, 12138, 12139, 12140, 12141, 12142, and 12143 constitutes the proceedings of the 20th International Conference on Computational Science, ICCS 2020, held in Amsterdam, The Netherlands, in June 2020.* The total of 101 papers and 248 workshop papers presented in this book set were carefully reviewed and selected from 719 submissions (230 submissions to the main track and 489 submissions to the workshops). The papers were organized in topical sections named: Part I: ICCS Main Track Part II: ICCS Main Track Part III: Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Agent-Based Simulations, Adaptive Algorithms and Solvers; Applications of Computational Methods in Artificial Intelligence and Machine Learning; Biomedical and Bioinformatics Challenges for Computer Science Part IV: Classifier Learning from Difficult Data; Complex Social Systems through the Lens of Computational Science; Computational Health; Computational Methods for Emerging Problems in (Dis-)Information Analysis Part V: Computational Optimization, Modelling and Simulation; Computational Science in IoT and Smart Systems; Computer Graphics, Image Processing and Artificial Intelligence Part VI: Data Driven Computational Sciences; Machine Learning and Data Assimilation for Dynamical Systems; Meshfree Methods in Computational Sciences; Multiscale Modelling and Simulation; Quantum Computing Workshop Part VII: Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks and Machine Learning; Software Engineering for Computational Science; Solving Problems with Uncertainties; Teaching Computational Science; UNcErtainty QUantIficatiOn for ComputationAl modeLs *The conference was canceled due to the COVID-19 pandemic.
Author: Leonid Karlinsky Publisher: Springer Nature ISBN: 3031250699 Category : Computers Languages : en Pages : 796
Book Description
The 8-volume set, comprising the LNCS books 13801 until 13809, constitutes the refereed proceedings of 38 out of the 60 workshops held at the 17th European Conference on Computer Vision, ECCV 2022. The conference took place in Tel Aviv, Israel, during October 23-27, 2022; the workshops were held hybrid or online. The 367 full papers included in this volume set were carefully reviewed and selected for inclusion in the ECCV 2022 workshop proceedings. They were organized in individual parts as follows: Part I: W01 - AI for Space; W02 - Vision for Art; W03 - Adversarial Robustness in the Real World; W04 - Autonomous Vehicle Vision Part II: W05 - Learning With Limited and Imperfect Data; W06 - Advances in Image Manipulation; Part III: W07 - Medical Computer Vision; W08 - Computer Vision for Metaverse; W09 - Self-Supervised Learning: What Is Next?; Part IV: W10 - Self-Supervised Learning for Next-Generation Industry-Level Autonomous Driving; W11 - ISIC Skin Image Analysis; W12 - Cross-Modal Human-Robot Interaction; W13 - Text in Everything; W14 - BioImage Computing; W15 - Visual Object-Oriented Learning Meets Interaction: Discovery, Representations, and Applications; W16 - AI for Creative Video Editing and Understanding; W17 - Visual Inductive Priors for Data-Efficient Deep Learning; W18 - Mobile Intelligent Photography and Imaging; Part V: W19 - People Analysis: From Face, Body and Fashion to 3D Virtual Avatars; W20 - Safe Artificial Intelligence for Automated Driving; W21 - Real-World Surveillance: Applications and Challenges; W22 - Affective Behavior Analysis In-the-Wild; Part VI: W23 - Visual Perception for Navigation in Human Environments: The JackRabbot Human Body Pose Dataset and Benchmark; W24 - Distributed Smart Cameras; W25 - Causality in Vision; W26 - In-Vehicle Sensing and Monitorization; W27 - Assistive Computer Vision and Robotics; W28 - Computational Aspects of Deep Learning; Part VII: W29 - Computer Vision for Civil and Infrastructure Engineering; W30 - AI-Enabled Medical Image Analysis: Digital Pathology and Radiology/COVID19; W31 - Compositional and Multimodal Perception; Part VIII: W32 - Uncertainty Quantification for Computer Vision; W33 - Recovering 6D Object Pose; W34 - Drawings and Abstract Imagery: Representation and Analysis; W35 - Sign Language Understanding; W36 - A Challenge for Out-of-Distribution Generalization in Computer Vision; W37 - Vision With Biased or Scarce Data; W38 - Visual Object Tracking Challenge.
Author: Asit Kumar Das Publisher: Springer Nature ISBN: 9819937345 Category : Technology & Engineering Languages : en Pages : 748
Book Description
This book features high-quality research papers presented at the 5th International Conference on Computational Intelligence in Pattern Recognition (CIPR 2023), held at Department of Computer Science and Engineering, Techno Main Salt Lake, West Bengal, India, during May 27–28, 2023. It includes practical development experiences in various areas of data analysis and pattern recognition, focusing on soft computing technologies, clustering and classification algorithms, rough set and fuzzy set theory, evolutionary computations, neural science and neural network systems, image processing, combinatorial pattern matching, social network analysis, audio and video data analysis, data mining in dynamic environments, bioinformatics, hybrid computing, big data analytics, and deep learning. It also provides innovative solutions to the challenges in these areas and discusses recent developments.
Author: Lazaros Iliadis Publisher: Springer Nature ISBN: 3031441958 Category : Computers Languages : en Pages : 559
Book Description
The 10-volume set LNCS 14254-14263 constitutes the proceedings of the 32nd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2023, which took place in Heraklion, Crete, Greece, during September 26–29, 2023. The 426 full papers, 9 short papers and 9 abstract papers included in these proceedings were carefully reviewed and selected from 947 submissions. ICANN is a dual-track conference, featuring tracks in brain inspired computing on the one hand, and machine learning on the other, with strong cross-disciplinary interactions and applications.
Author: João Manuel R. S. Tavares
Author: João Manuel R. S. Tavares
Author: Eva Irene Brooks
Author: João Manuel R. S. Tavares
Author: Jyotismita Chaki
Author: Hitoshi Iba
Author: Sebastia Massanet
Author: Valeria V. Krzhizhanovskaya
Author: Leonid Karlinsky
Author: Asit Kumar Das
Author: Lazaros Iliadis