الصفحة 1
الصفحة 1
Object-Based Image Analysis and Treaty Verification : New Approaches in Remote Sensing – Applied to Nuclear Facilities in Iran
This book describes recent progress in object-based image interpretation, and also presents many new results in its application to verification of nuclear non-proliferation. A comprehensive workflow and newly developed algorithms for object-based high resolution image (pre-) processing, feature extraction, change detection, classification and interpretation are developed, applied and evaluated. The entire analysis chain is demonstrated with high resolution imagery acquired over Iranian nuclear facilities.
Object-Based Image Analysis : Spatial Concepts for Knowledge-Driven Remote Sensing Applications
This book discusses means, technologies and approaches related to the processing and analysis of multi-sensor, multi-resolution data with a focus on the generation, modelling and classification of objects. The applications also address the integration of Geographic Information and the concurrent developments of GIScience and vanquish limitations of pixelwise image processing by exploiting image information context-driven and "intelligently".
New frontiers in artificial intelligence ; JSAI-isAI International Workshops, JURISIN, AI-Biz, LENLS, Kansei-AI, Yokohama, Japan, November 10–12, 2019, Revised Selected Papers
This book constitutes extended, revised and selected papers from the 11th International Symposium of Artificial Intelligence supported by the Japanese Society for Artificial Intelligence, JSAI-isAI 2019. It was held in November 2019 in Yokohama, Japan. The 26 papers were carefully selected from 46 submissions and deal with topics of AI research and are organized into 4 sections, according to the 4 workshops: JURISIN 2019, AI-Biz 2019, LENLS 16, and Kansei-AI 2019.
Neural Networks : Computational Models and Applications
Neural Networks: Computational Models and Applications covers a wealth of important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications in broad manifolds of computational intelligence: pattern recognition, uniform approximation, constrained optimization, NP-hard problems, and image segmentation. By presenting various computational models, this book is developed to provide readers with a quick but insightful understanding of the broad and rapidly growing areas in the neural networks domain. Besides laying down fundamentals on artificial neural networks, this book also studies biologically inspired neural networks. Some typical computational models are discussed, and subsequently applied to objection recognition, scene analysis and associative memory. The studies of bio-inspired models have important implications in computer vision and robotic navigation, as well as new efficient algorithms for image analysis.
Multiscale Modeling : A Bayesian Perspective
The book is aimed at statisticians, applied mathematicians, and engineers working on problems dealing with multiscale processes in time and/or space, such as in engineering, finance, and environmetrics. The book will also be of interest to those working on multiscale computation research. The main prerequisites are knowledge of Bayesian statistics and basic Markov chain Monte Carlo methods. A number of real-world examples are thoroughly analyzed in order to demonstrate the methods and to assist the readers in applying these methods to their own work. To further assist readers, the authors are making source code (for R) available for many of the basic methods discussed herein.
Multiple Classifier Systems ; 6th International Workshop, MCS 2005, Seaside, CA, USA, June 13-15, 2005, Proceedings
Constitutes the refereed proceedings of the 6th International Workshop on Multiple Classifier Systems, MCS 2005. This book contains papers that are organized in topical sections on boosting, combination methods, performance analysis, and applications. They exemplify the advances in the theory and applications of multiple classifier systems
Multiple Classifier Systems ; 2nd International Workshop, MCS 2001 Cambridge, UK, July 2-4, 2001 Proceedings
Driven by the requirements of a large number of practical and commercially - portant applications, the last decade has witnessed considerable advances in p- tern recognition. Better understanding of the design issues and new paradigms, such as the Support Vector Machine, have contributed to the development of - proved methods of pattern classi cation. However, while any performance gains are welcome, and often extremely signi cant from the practical point of view, it is increasingly more challenging to reach the point of perfection as de ned by the theoretical optimality of decision making in a given decision framework. The asymptoticity of gains that can be made for a single classi er is a re?- tion of the fact that any particular design, regardless of how good it is, simply provides just one estimate of the optimal decision rule.
Multimedia technology and enhanced learning ; 2nd EAI International conference, ICMTEL 2020, Leicester, UK, April 10-11, 2020, Proceedings, Part II
This two-volume book constitutes the refereed proceedings of the Second International Conference on Multimedia Technology and Enhanced Learning, ICMTEL 2020, held in Leicester, United Kingdom, in April 2020. Due to the COVID-19 pandemic all papers were presented in YouTubeLive. The 83 revised full papers have been selected from 158 submissions. They describe new learning technologies which range from smart school, smart class and smart learning at home and which have been developed from new technologies such as machine learning, multimedia and Internet of Things.
Multimedia Technology and Enhanced Learning ; 2nd EAI International Conference, ICMTEL 2020, Leicester, UK, April 10-11, 2020, Proceedings, Part I
This two-volume book constitutes the refereed proceedings of the Second International Conference on Multimedia Technology and Enhanced Learning, ICMTEL 2020, held in Leicester, United Kingdom, in April 2020. Due to the COVID-19 pandemic all papers were presented in YouTubeLive. The 83 revised full papers have been selected from 158 submissions. They describe new learning technologies which range from smart school, smart class and smart learning at home and which have been developed from new technologies such as machine learning, multimedia and Internet of Things.
Multimedia Content Representation, Classification and Security ; International Workshop, MRCS 2006, Istanbul, Turkey, September 11-13, 2006, Proceedings
This book constitutes the refereed proceedings of the International Workshop on Multimedia Content Representation, Classification and Security, MRCS 2006, held in Istanbul, Turkey in September 2006. The 100 revised papers presented together with 4 invited lectures were carefully reviewed and selected from more than 190 submissions. The papers are organized in topical sections on biometric recognition, multimedia content security, steganography, watermarking, authentication, classification for biometric recognition, digital watermarking, content analysis and representation, 3D object retrieval and classification, representation, analysis and retrieval in cultural heritage, content representation, indexing and retrieval, content analysis and classification, feature extraction and classification, multimodal signal processing, 3D video and free viewpoint video, multimedia content transmission and classification, video and image processing, as well as video analysis and representation.
MRI of the Heart and Vessels
In recent years magnetic resonance imaging (MRI) has enriched the technological potential available for the characterization of cardiovascular pathologies, adding substantial advantages to other non-invasive techniques. This technique, which is intrinsically digital and has reduced operator dependency, allows the performance of image analysis in a quantitative and reproducible manner. In virtue of its added diagnostic value and inherent refinements that allow construction of two- and three-dimensional images, MRI is gaining a primary role in the histopathological and physiopathological understanding of a large number of pathologies concerning the heart and vessels. This text is addressed both to MRI operators seeking specific technical information and to clinicians who wish to have a better understanding of the diagnostic and management advantages that MRI can offer.
Modélisation et statistique spatiales = Spatial modeling and statistics
Spatial statistics are undergoing significant development due to their use in many fields: earth sciences, environment and climatology, epidemiology, econometrics, image analysis, etc. This book presents the main spatial models used as well as their statistics for the three types of data: geostatistics (observation on a continuous domain), data on a discrete network, point data. The objective is to present in a concise but mathematically complete way the most classical models (second order and variogram; software model and Gibbs-Markov field; point processes) as well as their simulation by MCMC algorithm. Then comes the presentation of statistical tools useful for their study.
Methods of Cancer Diagnosis, Therapy and Prognosis : Breast Carcinoma
Focusing on Breast Carcinoma, this first volume in the series Methods of Cancer Diagnosis, Therapy and Prognosis brings together 56 leading scientists from around the world to deliver a comprehensive treatise on all aspects of breast cancer, including diagnosis, treatments and prognosis.
Medical Imaging and Augmented Reality ; 4th International Workshop Tokyo, Japan, August 1-2, 2008 Proceedings
Constitutes the refereed proceedings of the 4th International Workshop on Medical Imaging and Augmented Reality, MIAR 2008, held in Tokyo, Japan, in August 2008.The 44 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 90 submissions. The papers are organized in topical sections on surgical planning and simulation, medical image computing, image analysis, shape modeling and morphometry, image-guided robotics, image-guided intervention, interventional imaging, image registration, augmented reality, and image segmentation.
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2008 ; 11th International Conference, New York, NY, USA, September 6-10, 2008, Proceedings, Part I
The program committee carefully selected 258 revised papers from numerous submissions for presentation in two volumes, based on rigorous peer reviews. The first volume includes 127 papers related to medical image computing, segmentation, shape and statistics analysis, modeling, motion tracking and compensation, as well as registration. The second volume contains 131 contributions related to robotics and interventions, statistical analysis, segmentation, intervention, modeling, and registration.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006 ; Vol. 4191; 9th International Conference, Copenhagen, Denmark, October 1-6, 2006, Proceedings, Part II
T MICCAI papers are of high standard and have a long lifetime. In this v- ume as well as in the latest journal issues of Medical Image Analysis and IEEE Transactions on Medical Imaging papers cite previous MICCAIs including the ?rst MICCAI conference in Cambridge, Massachusetts, 1998. It is obvious that the community requires the MICCAI papers as archive material. Therefore the proceedingsofMICCAIarefrom2005andhenceforthbeing indexedbyMedline. Acarefulreviewandselectionprocesswasexecutedinordertosecurethebest possible program for the MICCAI 2006 conference. We received 578 scienti?c papers from which 39 papers were selected for the oral program and 193 papers for the poster program.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006 ; Vol. 4190 ; 9th International Conference, Copenhagen, Denmark, October 1-6, 2006, Proceedings, Part I
MICCAI papers are of high standard and have a long lifetime. In this v- ume as well as in the latest journal issues of Medical Image Analysis and IEEE Transactions on Medical Imaging papers cite previous MICCAIs including the ?rst MICCAI conference in Cambridge, Massachusetts, 1998. It is obvious that the community requires the MICCAI papers as archive material. Therefore the proceedingsofMICCAIarefrom2005andhenceforthbeing indexedbyMedline. Acarefulreviewandselectionprocesswasexecutedinordertosecurethebest possible program for the MICCAI 2006 conference. We received 578 scienti?c papers from which 39 papers were selected for the oral program and 193 papers for the poster program.
Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2005 ; 8th International Conference, Palm Springs, CA, USA, October 26-29, 2005, Proceedings, Part II
Robotics, Image-Guided Surgery and Interventions -- Image Registration II -- Medical Image Computing -- Atlases -- Shape I -- Structural and Functional Brain Analysis -- Model-Based Image Analysis -- Image-Guided Intervention: Simulation, Modeling and Display -- Simulation and Modeling II -- Medical Image Computing -- Shape II -- Image Segmentation and Analysis II -- Image Registration III --
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005 ; 8th International Conference, Palm Springs, CA, USA, October 26-29, 2005, Proceedings, Part I
This paper presents a method for classification of medical images, using machine learning and deformation-based morphometry. A morphological representation of the anatomy of interest is first obtained using highdimensional template warping, from which regions that display strong correlations between morphological measurements and the classification (clinical) variable are extracted using a watershed segmentation, taking into account the regional smoothness of the correlation map which is estimated by a crossvalidation strategy in order to achieve robustness to outliers. A Support Vector Machine-Recursive Feature Elimination (SVM-RFE) technique is then used to rank computed features from the extracted regions, according to their effect on the leave-one-out error bound. Finally, SVM classification is applied using the best set of features, and it is tested using leave-one-out. The results from a group of 61 brain images of female normal controls and schizophrenia patients demonstrate not only high classification accuracy (91.8%) and steep ROC curves, but also exceptional stability with respect to the number of selected features and the SVM kernel size
Medical data processing and analysis
Medical data can be defined as obtaining information from patients (such as signals, images, sounds, chemical components and their concentration, body temperature, respiratory rate, blood pressure, and different treatment measurements) to quantify the patient’s status and disease stage. Computer-aided diagnostic (CAD) systems use classical image processing, computer vision, machine learning, and deep learning methods for image analysis. Using image classification or segmentation algorithms, they find a region of interest (ROI) pointing to a specific location within the given image or an outcome of interest in the form of a label pointing to a diagnosis or prognosis. Computer science, with the evolution of artificial intelligence and machine learning techniques, facilitates the modeling and interpretation of results—from carrying out measurements to experiments and observations.
