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Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support, Kenji Suzuki; Mauricio Reyes; Tanveer Syeda-Mahmoo


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Автор: Kenji Suzuki; Mauricio Reyes; Tanveer Syeda-Mahmoo
Название:  Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support
ISBN: 9783030338497
Издательство: Springer
Классификация:




ISBN-10: 3030338495
Обложка/Формат: Soft cover
Страницы: 93
Вес: 0.19 кг.
Дата издания: 2019
Серия: Image Processing, Computer Vision, Pattern Recognition, and Graphics
Язык: English
Издание: 1st ed. 2019
Иллюстрации: 35 illustrations, color; 33 illustrations, black and white; xvi, 93 p. 68 illus., 35 illus. in color.
Размер: 234 x 156 x 6
Читательская аудитория: Professional & vocational
Основная тема: Computer Science
Подзаголовок: Second International Workshop, iMIMIC 2019, and 9th International Workshop, ML-CDS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание:

Second International Workshop on Interpretability of Machine Intelligence in Medical Image Computing (iMIMIC 2019).- Testing the robustness of attribution methods for convolutional neural networks in MRI-based Alzheimers disease classification.- UBS: A Dimension-Agnostic Metric for Concept Vector Interpretability Applied to Radiomics.- Generation of Multimodal Justification Using Visual Word Constraint Model for Explainable Computer-Aided Diagnosis.- Incorporating Task-Specific Structural Knowledge into CNNs for Brain Midline Shift Detection.- Guideline-based Additive Explanation for Computer-Aided Diagnosis of Lung Nodules.- Deep neural network or dermatologist?.- Towards Interpretability of Segmentation Networks by analyzing DeepDreams.- 9th International Workshop on Multimodal Learning for Clinical Decision Support (ML-CDS 2019).- Towards Automatic Diagnosis from Multi-modal Medical Data.- Deep Learning based Multi-Modal Registration for Retinal Imaging.- Automated Enriched Medical Concept Generation for Chest X-ray Images.


Дополнительное описание: Second International Workshop on Interpretability of Machine Intelligence in Medical Image Computing (iMIMIC 2019).- Testing the robustness of attribution methods for convolutional neural networks in MRI-based Alzheimer's disease classification.- UBS: A D



Interpretability of Computational Intelligence-Based Regression Models

Автор: Tam?s Kenesei; J?nos Abonyi
Название: Interpretability of Computational Intelligence-Based Regression Models
ISBN: 3319219413 ISBN-13(EAN): 9783319219417
Издательство: Springer
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Цена: 6986.00 р.
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Описание: The key idea of this book is that hinging hyperplanes, neural networks and support vector machines can be transformed into fuzzy models, and interpretability of the resulting rule-based systems can be ensured by special model reduction and visualization techniques.

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

Автор: Danail Stoyanov; Zeike Taylor; Gustavo Carneiro; T
Название: Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support
ISBN: 3030008886 ISBN-13(EAN): 9783030008888
Издательство: Springer
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Цена: 9222.00 р.
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Описание: This book constitutes the refereed joint proceedings of the 4th International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2018, and the 8th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018.The 39 full papers presented at DLMIA 2018 and the 4 full papers presented at ML-CDS 2018 were carefully reviewed and selected from 85 submissions to DLMIA and 6 submissions to ML-CDS. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

Автор: M. Jorge Cardoso; Tal Arbel; Gustavo Carneiro; Tan
Название: Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support
ISBN: 3319675575 ISBN-13(EAN): 9783319675572
Издательство: Springer
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Цена: 9083.00 р.
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Описание:

This book constitutes the refereed joint proceedings of the Third International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017, and the 6th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017.

The 38 full papers presented at DLMIA 2017 and the 5 full papers presented at ML-CDS 2017 were carefully reviewed and selected. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.

Multimodal Retrieval in the Medical Domain

Автор: Henning M?ller; Oscar Alfonso Jimenez del Toro; Al
Название: Multimodal Retrieval in the Medical Domain
ISBN: 3319244701 ISBN-13(EAN): 9783319244709
Издательство: Springer
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Цена: 5590.00 р.
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Описание: This book constitutes the proceedings of the First International Workshop on Multimodal Retrieval in the Medical Domain, MRMD 2015, held in Vienna, Austria, on March 29, 2015.

Multiscale Multimodal Medical Imaging

Автор: Quanzheng Li; Richard Leahy; Bin Dong; Xiang Li
Название: Multiscale Multimodal Medical Imaging
ISBN: 303037968X ISBN-13(EAN): 9783030379681
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This book constitutes the refereed proceedings of the First International Workshop on Multiscale Multimodal Medical Imaging, MMMI 2019, held in conjunction with MICCAI 2019 in Shenzhen, China, in October 2019. The 13 papers presented were carefully reviewed and selected from 18 submissions.

Machine Learning for Multimodal Interaction

Автор: Andrei Popescu-Belis; Rainer Stiefelhagen
Название: Machine Learning for Multimodal Interaction
ISBN: 3540858520 ISBN-13(EAN): 9783540858522
Издательство: Springer
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Цена: 10480.00 р.
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Описание: Constitutes the refereed proceedings of the 5th International Workshop on Machine Learning for Multimodal Interaction, MLMI 2008, held in Utrecht, The Netherlands, in September 2008. This title features papers that cover a wide range of topics related to human-human communication modeling and processing, as well as to human-computer interaction.

Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction

Автор: Ronald B?ck; Francesca Bonin; Nick Campbell; Ronal
Название: Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction
ISBN: 3319155563 ISBN-13(EAN): 9783319155562
Издательство: Springer
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Цена: 5590.00 р.
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Описание:

Annotating the TCD D-ANS Corpus - A Multimodal Multimedia Monolingual Biometric Corpus of Spoken Social Interaction.- Steps Towards More Natural Human-Machine Interaction via Audio-Visual Word Prominence Detection.- Improving Robustness Against Environmental Sounds for Directing Attention of Social Robots.- On Annotation and Evaluation of Multi-modal Corpora in Affective Human-Computer Interaction.- Modelling User Experience in Human-Robot Interactions.- Disposition Recognition from Spontaneous Speech Towards a Combination with Co-speech Gestures.- ASR Independent Hybrid Recurrent Neural Network Based Error Correction for Dialog System Applications.- Acquisition and Use of Long-Term Memory for Personalized Dialog Systems.- An Automatic Shout Detection System Using Speech Production Features.- Collecting Data for Automatic Speech Recognition Systems in Dialectal Arabic Using Games with a Purpose.- A Multimodal Multimedia Monolingual Biometric Corpus of Spoken Social Interaction.- Steps Towards More Natural Human-Machine Interaction via Audio-Visual Word Prominence Detection.- Improving Robustness Against Environmental Sounds for Directing Attention of Social Robots.- On Annotation and Evaluation of Multi-modal Corpora in Affective Human-Computer Interaction.- Modelling User Experience in Human-Robot Interactions.-Disposition Recognition from Spontaneous Speech Towards a Combination with Co-speech Gestures.- ASR Independent Hybrid Recurrent Neural Network Based Error Correction for Dialog System Applications.- Acquisition and Use of Long-Term Memory for Personalized Dialog Systems.- An Automatic Shout Detection System Using Speech Production Features.- Collecting Data for Automatic Speech Recognition Systems in Dialectal Arabic Using Games with a Purpose.

Multimodal Interaction in Image and Video Applications

Автор: Angel D. Sappa; Jordi Vitri?
Название: Multimodal Interaction in Image and Video Applications
ISBN: 3642359310 ISBN-13(EAN): 9783642359316
Издательство: Springer
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Цена: 19591.00 р.
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Описание: This book shows case studies of multimodal interactive technologies for both image and video applications. They cover a wide spectrum of applications, ranging from interactive handwriting transcriptions to human-robot interactions in real environments.

Multimodal Interaction in Image and Video Applications

Автор: Angel D. Sappa; Jordi Vitri?
Название: Multimodal Interaction in Image and Video Applications
ISBN: 3642439837 ISBN-13(EAN): 9783642439834
Издательство: Springer
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Цена: 16977.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book shows case studies of multimodal interactive technologies for both image and video applications. They cover a wide spectrum of applications, ranging from interactive handwriting transcriptions to human-robot interactions in real environments.

Multimodal Biometrics And Intelligent Image Processing For Security System

Автор: Gavrilova & Monwar
Название: Multimodal Biometrics And Intelligent Image Processing For Security System
ISBN: 1466636467 ISBN-13(EAN): 9781466636460
Издательство: Mare Nostrum (Eurospan)
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Цена: 28413.00 р.
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Описание: Although it is a relatively new approach to biometric knowledge representation, multimodal biometric systems have emerged as an innovative alternative that aids in developing a more reliable and efficient security system. <br><br><em>Multimodal Biometrics and Intelligent Image Processing for Security Systems</em> provides an in-depth description of existing and fresh fusion approaches for multimodal biometric systems. Covering relevant topics affecting the security and intelligent industries, this reference will be useful for readers from both academia and industry in the areas of pattern recognition, security, and image processing domains.

Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy

Автор: Dajiang Zhu; Jingwen Yan; Heng Huang; Li Shen; Pau
Название: Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy
ISBN: 303033225X ISBN-13(EAN): 9783030332259
Издательство: Springer
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Цена: 8104.00 р.
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Описание: MBIA.- Non-rigid Registration of White Matter Tractography Using Coherent Point Drift Algorithm.- An Edge Enhanced SRGAN for MRI Super Resolution in Slice-selection Direction.- Exploring Functional Connectivity Biomarker in Autism Using Group-wise Sparse Representation.- Classifying Stages of Mild Cognitive Impairment via Augmented Graph Embedding.- Mapping the spatio-temporal functional coherence in the resting brain.- Species-Preserved Structural Connections Revealed by Sparse Tensor CCA.- Identification of Abnormal Cortical 3-hinge Folding Patterns on Autism Spectral Brains.- Exploring Brain Hemodynamic Response Patterns Via Deep Recurrent Autoencoder.- 3D Convolutional Long-short Term Memory Network for Spatiotemporal Modeling of fMRI Data.- Biological Knowledge Guided Deep Neural Network for Genotype-Phenotype Association Study.- Learning Human Cognition via fMRI Analysis Using 3D CNN and Graph Neural Network.- CU-Net: Cascaded U-Net with Loss Weighted Sampling for Brain Tumor Segmentation.- BrainPainter: A software for the visualisation of brain structures, biomarkers and associated pathological processes.- Structural Similarity based Anatomical and Functional Brain Imaging Fusion.- Multimodal Brain Tumor Segmentation Using Encoder-Decoder with Hierarchical Separable Convolution.- Prioritizing Amyloid Imaging Biomarkers in Alzheimer's Disease via Learning to Rank.- MFCA.- Diffeomorphic Metric Learning and Template Optimization for Registration-Based Predictive Models.- 3D mapping of serial histology sections with anomalies using a novel robust deformable registration algorithm.- Spatiotemporal Modeling for Image Time Series with Appearance Change: Application to Early Brain Development.- Surface Foliation Based Brain Morphometry Analysis.- Mixture Probabilistic Principal Geodesic Analysis.- A Geodesic Mixed Effects Model in Kendall's Shape Space.- An as-invariant-as-possible GL+(3)-based Statistical Shape Model.

Multimodal Brain Image Analysis

Автор: Li Shen; Tianming Liu; Pew-Thian Yap; Heng Huang;
Название: Multimodal Brain Image Analysis
ISBN: 3319021257 ISBN-13(EAN): 9783319021256
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This book constitutes the refereed proceedings of the Third International Workshop on Multimodal Brain Image Analysis, MBIA 2013, held in Nagoya, Japan, on September 22, 2013 in conjunction with the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI.


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