Computer Information Systems and Industrial Management

Computer Information Systems and Industrial Management PDF Author: Khalid Saeed
Publisher: Springer
ISBN: 3642409253
Category : Computers
Languages : en
Pages : 541

Get Book Here

Book Description
This book constitutes the proceedings of the 12th IFIP TC 8 International Conference, CISIM 2013, held in Cracow, Poland, in September 2013. The 44 papers presented in this volume were carefully reviewed and selected from over 60 submissions. They are organized in topical sections on biometric and biomedical applications; pattern recognition and image processing; various aspects of computer security, networking, algorithms, and industrial applications. The book also contains full papers of a keynote speech and the invited talk.

Computer Information Systems and Industrial Management

Computer Information Systems and Industrial Management PDF Author: Khalid Saeed
Publisher: Springer
ISBN: 3642409253
Category : Computers
Languages : en
Pages : 541

Get Book Here

Book Description
This book constitutes the proceedings of the 12th IFIP TC 8 International Conference, CISIM 2013, held in Cracow, Poland, in September 2013. The 44 papers presented in this volume were carefully reviewed and selected from over 60 submissions. They are organized in topical sections on biometric and biomedical applications; pattern recognition and image processing; various aspects of computer security, networking, algorithms, and industrial applications. The book also contains full papers of a keynote speech and the invited talk.

Bayesian Learning for Neural Networks

Bayesian Learning for Neural Networks PDF Author: Radford M. Neal
Publisher: Springer Science & Business Media
ISBN: 1461207452
Category : Mathematics
Languages : en
Pages : 194

Get Book Here

Book Description
Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions remain about how the power of these models can be safely exploited when training data is limited. This book demonstrates how Bayesian methods allow complex neural network models to be used without fear of the "overfitting" that can occur with traditional training methods. Insight into the nature of these complex Bayesian models is provided by a theoretical investigation of the priors over functions that underlie them. A practical implementation of Bayesian neural network learning using Markov chain Monte Carlo methods is also described, and software for it is freely available over the Internet. Presupposing only basic knowledge of probability and statistics, this book should be of interest to researchers in statistics, engineering, and artificial intelligence.

Business Process Management

Business Process Management PDF Author: Artem Polyvyanyy
Publisher: Springer Nature
ISBN: 3030854698
Category : Computers
Languages : en
Pages : 480

Get Book Here

Book Description
This volume constitutes the refereed proceedings of the 19th International Conference on Business Process Management, BPM 2021, held in Rome, Italy, in September 2021. The 23 full papers, one keynote paper, and 4 tutorial papers presented in this volume were carefully reviewed and selected from 92 submissions. The papers are organized in topical sections named: foundations, engineering, and management.

Shape, Contour and Grouping in Computer Vision

Shape, Contour and Grouping in Computer Vision PDF Author: David A. Forsyth
Publisher: Springer Science & Business Media
ISBN: 3540667229
Category : Computers
Languages : en
Pages : 340

Get Book Here

Book Description
Computer vision has been successful in several important applications recently. Vision techniques can now be used to build very good models of buildings from pictures quickly and easily, to overlay operation planning data on a neuros- geon’s view of a patient, and to recognise some of the gestures a user makes to a computer. Object recognition remains a very di cult problem, however. The key questions to understand in recognition seem to be: (1) how objects should be represented and (2) how to manage the line of reasoning that stretches from image data to object identity. An important part of the process of recognition { perhaps, almost all of it { involves assembling bits of image information into helpful groups. There is a wide variety of possible criteria by which these groups could be established { a set of edge points that has a symmetry could be one useful group; others might be a collection of pixels shaded in a particular way, or a set of pixels with coherent colour or texture. Discussing this process of grouping requires a detailed understanding of the relationship between what is seen in the image and what is actually out there in the world.

Advances in Intelligent Data Analysis XIX

Advances in Intelligent Data Analysis XIX PDF Author: Pedro Henriques Abreu
Publisher: Springer Nature
ISBN: 3030742512
Category : Computers
Languages : en
Pages : 454

Get Book Here

Book Description
This book constitutes the proceedings of the 19th International Symposium on Intelligent Data Analysis, IDA 2021, which was planned to take place in Porto, Portugal. Due to the COVID-19 pandemic the conference was held online during April 26-28, 2021. The 35 papers included in this book were carefully reviewed and selected from 113 submissions. The papers were organized in topical sections named: modeling with neural networks; modeling with statistical learning; modeling language and graphs; and modeling special data formats.

Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures

Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures PDF Author: Hayit Greenspan
Publisher: Springer Nature
ISBN: 3030326896
Category : Computers
Languages : en
Pages : 202

Get Book Here

Book Description
This book constitutes the refereed proceedings of the First International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2019, and the 8th International Workshop on Clinical Image-Based Procedures, CLIP 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. For UNSURE 2019, 8 papers from 15 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world. CLIP 2019 accepted 11 papers from the 15 submissions received. The workshops provides a forum for work centred on specific clinical applications, including techniques and procedures based on comprehensive clinical image and other data.

Artificial Neural Network Modelling

Artificial Neural Network Modelling PDF Author: Subana Shanmuganathan
Publisher: Springer
ISBN: 3319284959
Category : Technology & Engineering
Languages : en
Pages : 468

Get Book Here

Book Description
This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling.

Advances in Intelligent Data Analysis XVIII

Advances in Intelligent Data Analysis XVIII PDF Author: Michael R. Berthold
Publisher: Springer
ISBN: 9783030445836
Category : Computers
Languages : en
Pages : 588

Get Book Here

Book Description
This open access book constitutes the proceedings of the 18th International Conference on Intelligent Data Analysis, IDA 2020, held in Konstanz, Germany, in April 2020. The 45 full papers presented in this volume were carefully reviewed and selected from 114 submissions. Advancing Intelligent Data Analysis requires novel, potentially game-changing ideas. IDA’s mission is to promote ideas over performance: a solid motivation can be as convincing as exhaustive empirical evaluation.

Machine Learning in Chemistry

Machine Learning in Chemistry PDF Author: Jon Paul Janet
Publisher: American Chemical Society
ISBN: 0841299005
Category : Science
Languages : en
Pages : 189

Get Book Here

Book Description
Recent advances in machine learning or artificial intelligence for vision and natural language processing that have enabled the development of new technologies such as personal assistants or self-driving cars have brought machine learning and artificial intelligence to the forefront of popular culture. The accumulation of these algorithmic advances along with the increasing availability of large data sets and readily available high performance computing has played an important role in bringing machine learning applications to such a wide range of disciplines. Given the emphasis in the chemical sciences on the relationship between structure and function, whether in biochemistry or in materials chemistry, adoption of machine learning by chemistsderivations where they are important

Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis

Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis PDF Author: Carole H. Sudre
Publisher: Springer Nature
ISBN: 3030603652
Category : Computers
Languages : en
Pages : 233

Get Book Here

Book Description
This book constitutes the refereed proceedings of the Second International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2020, and the Third International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The workshops were held virtually due to the COVID-19 pandemic. For UNSURE 2020, 10 papers from 18 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world. GRAIL 2020 accepted 10 papers from the 12 submissions received. The workshop aims to bring together scientists that use and develop graph-based models for the analysis of biomedical images and to encourage the exploration of graph-based models for difficult clinical problems within a variety of biomedical imaging contexts.