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Computer Vision – ECCV 2022
The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015
The three-volume set LNCS 9349, 9350, and 9351 constitutes the refereed proceedings of the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015, held in Munich, Germany, in October 2015. Based on rigorous peer reviews, the program committee carefully selected 263 revised papers from 810 submissions for presentation in three volumes. The papers have been organized in the following topical sections: quantitative image analysis I: segmentation and measurement; computer-aided diagnosis: machine learning; computer-aided diagnosis: automation; quantitative image analysis II: classification, detection, features, and morphology; advanced MRI: diffusion, fMRI, DCE; quantitative image analysis III: motion, deformation, development and degeneration; quantitative image analysis IV: microscopy, fluorescence and histological imagery; registration: method and advanced applications; reconstruction, image formation, advanced acquisition - computational imaging; modelling and simulation for diagnosis and interventional planning; computer-assisted and image-guided interventions.
Intelligence Science I
This book constitutes the refereed proceedings of the Second International Conference on Intelligence Science, ICIS 2017, held in Shanghai, China, in October 2017. The 38 full papers and 9 short papers presented were carefully reviewed and selected from 82 submissions. They deal with key issues in intelligence science and have been organized in the following topical sections: theory of intelligence science; cognitive computing; big data analysis and machine learning; machine perception; intelligent information processing; and intelligent applications.
Intelligent Data Engineering and Automated Learning - IDEAL 2009
The IDEAL conference boast a vibrant and successful history dating back to 1998, th and this edition marked the 10 anniversary, an important milestone demonstrating the increasing popularity and high quality of the IDEAL conferences. Burgos, the capital of medieval Spain and a lively city today, was a perfect venue to celebrate such an occasion. The conference has become a unique, established and broad int- disciplinary forum for researchers and practitioners in many fields to interact with each other and with leading academics and industries in the areas of machine lea- ing, information processing, data mining, knowledge management, bio-informatics, neuro-informatics, bio-inspired models, a...
Machine Learning in Medical Imaging
This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning in Medical Imaging, MLMI 2012, held in conjunction with MICCAI 2012, in Nice, France, in October 2012. The 33 revised full papers presented were carefully reviewed and selected from 67 submissions. The main aim of this workshop is to help advance the scientific research within the broad field of machine learning in medical imaging. It focuses on major trends and challenges in this area, and it presents work aimed to identify new cutting-edge techniques and their use in medical imaging.
Machine Learning in Medical Imaging
This book constitutes the refereed proceedings of the 5th International Workshop on Machine Learning in Medical Imaging, MLMI 2014, held in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2014, in Cambridge, MA, USA, in September 2014. The 40 contributions included in this volume were carefully reviewed and selected from 70 submissions. They focus on major trends and challenges in the area of machine learning in medical imaging and aim to identify new cutting-edge techniques and their use in medical imaging.
Machine Learning in Radiation Oncology
This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.
Big Data
This book constitutes the refereed proceedings of the 11th CCF Conference on BigData 2023, which took place in Nanjing, China, in September 2023. The 14 full papers presented in this volume were carefully reviewed and selected from 69 submissions. The topics of accepted papers include theories and methods of data science, algorithms and applications of big data.
Intelligent Data Engineering and Automated Learning – IDEAL 2016
This book constitutes the refereed proceedings of the 17 International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2016, held in Yangzhou, China, in October 2016. The 68 full papers presented were carefully reviewed and selected from 115 submissions. They provide a valuable and timely sample of latest research outcomes in data engineering and automated learning ranging from methodologies, frameworks, and techniques to applications including various topics such as evolutionary algorithms; deep learning; neural networks; probabilistic modeling; particle swarm intelligence; big data analysis; applications in regression, classification, clustering, medical and biological modeling and predication; text processing and image analysis.
