debdoot sheet (18 resultados)

Condición: New. pp. 84.

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Condición: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.

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Taschenbuch. Condición: Neu. Feature Usability Index | A Simple Approach to Feature Selection | Debdoot Sheet (u. a.) | Taschenbuch | 84 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783844303339 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the Third MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2021, and the First MICCAI Workshop on Affordable Healthcare and AI for Resource Diverse Global Health, FAIR 2021, held in conjunction with MICCAI 2021, in September/October 2021. The workshops were planned to take place in Strasbourg, France, but were held virtually due to the COVID-19 pandemic.DART 2021 accepted 13 papers from the 21 submissions received. The workshop aims at creating a discussion forum to compare, evaluate, and discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains. For FAIR 2021, 10 papers from 17 submissions were accepted for publication. They focus on Image-to-Image Translation particularly for low-dose or low-resolution settings; Model Compactness and Compression; Domain Adaptation and Transfer Learning; Active, Continual and Meta-Learning.

Condición: new. Questo è un articolo print on demand.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Feature selection as an area of interest within pattern recognition, deals with selection of a subset of attributes used in construction of a model describing observations. The purpose of this stage includes reducing data dimensionality by removing irrelevant and redundant features, reducing the amount of learning data, improving predictive accuracy and comprehensibility of a classification hypothesis. This book introduces Feature Usability Index (FUI) as a measure for evaluating classification efficacy of features and its application in feature selection. Experimental applications presents optimal feature subset selection through ordering based on FUI, use of FUI for ranking and selection of feature extraction techniques for a specific linguistic feature, and Color Usability Index as a measure for predicting performance of image segmentation algorithms. 84 pp. Englisch.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sheet DebdootDebdoot Sheet is currently working towards his Ph.D. degree at School of Medical Science and Technology, IIT Kharagpur.His research interests include image and multidimensional signal processing, pattern analysis and .

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the refereed proceedings of the Third MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2021, and the First MICCAI Workshop on Affordable Healthcare and AI for Resource Diverse Global Health, FAIR 2021, held in conjunction with MICCAI 2021, in September/October 2021. The workshops were planned to take place in Strasbourg, France, but were held virtually due to the COVID-19 pandemic.DART 2021 accepted 13 papers from the 21 submissions received. The workshop aims at creating a discussion forum to compare, evaluate, and discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains. For FAIR 2021, 10 papers from 17 submissions were accepted for publication. They focus on Image-to-Image Translation particularly for low-dose or low-resolution settings; Model Compactness and Compression; Domain Adaptation and Transfer Learning; Active, Continual and Meta-Learning. 280 pp. Englisch.

Condición: New. Print on Demand.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Feature selection as an area of interest within pattern recognition, deals with selection of a subset of attributes used in construction of a model describing observations. The purpose of this stage includes reducing data dimensionality by removing irrelevant and redundant features, reducing the amount of learning data, improving predictive accuracy and comprehensibility of a classification hypothesis. This book introduces Feature Usability Index (FUI) as a measure for evaluating classification efficacy of features and its application in feature selection. Experimental applications presents optimal feature subset selection through ordering based on FUI, use of FUI for ranking and selection of feature extraction techniques for a specific linguistic feature, and Color Usability Index as a measure for predicting performance of image segmentation algorithms.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 84 pp. Englisch.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Feature selection as an area of interest within pattern recognition, deals with selection of a subset of attributes used in construction of a model describing observations. The purpose of this stage includes reducing data dimensionality by removing irrelevant and redundant features, reducing the amount of learning data, improving predictive accuracy and comprehensibility of a classification hypothesis. This book introduces Feature Usability Index (FUI) as a measure for evaluating classification efficacy of features and its application in feature selection. Experimental applications presents optimal feature subset selection through ordering based on FUI, use of FUI for ranking and selection of feature extraction techniques for a specific linguistic feature, and Color Usability Index as a measure for predicting performance of image segmentation algorithms.

Condición: New. PRINT ON DEMAND.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book constitutes the refereed proceedings of the Third MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2021, and the First MICCAI Workshop on Affordable Healthcare and AI for Resource Diverse Global Health, FAIR 2021, held in con.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Domain Adaptation and Representation Transfer.- A Systematic Benchmarking Analysis of Transfer Learning for Medical Image Analysis.- Self-supervised Multi-scale Consistency for Weakly Supervised Segmentation Learning.- FDA: Feature Decomposition and Aggregation for Robust Airway Segmentation.- Adversarial Continual Learning for Multi-Domain Hippocampal Segmentation.- Self-Supervised Multimodal Generalized Zero Shot Learning For Gleason Grading.- Self-Supervised Learning of Inter-Label Geometric Relationships For Gleason Grade Segmentation.- Stop Throwing Away Discriminators! Re-using Adversaries for Test-Time Training.- Transductive image segmentation: Self-training and effect of uncertainty estimation.- Unsupervised Domain Adaptation with Semantic Consistency across Heterogeneous Modalities for MRI Prostate Lesion Segmentation.- Cohort Bias Adaptation in Federated Datasets for Lesion Segmentation.- Exploring Deep Registration Latent Spaces.- Learning from Partially Overlapping Labels: Image Segmentation under Annotation Shift.- Unsupervised Domain Adaption via Similarity-based Prototypes for Cross-Modality Segmentation.- A ordable AI and Healthcare.- Classification and Generation of Microscopy Images with Plasmodium Falciparum via Arti cial Neural Networks using Low Cost Settings.- Contrast and Resolution Improvement of POCUS Using Self-Consistent CycleGAN.- Low-Dose Dynamic CT Perfusion Denoising without Training Data.- Recurrent Brain Graph Mapper for Predicting Time-Dependent Brain Graph Evaluation Trajectory.- COVID-Net US: A Tailored, Highly Efficient, Self-Attention Deep Convolutional Neural Network Design for Detection of COVID-19Patient Cases from Point-of-care Ultrasound Imaging.- Inter-Domain Alignment for Predicting High-Resolution Brain Networks Using Teacher-Student Learning.- Sickle Cell Disease Severity Prediction from Percoll Gradient Images using Graph Convolutional Networks.- Continual Domain Incremental Learning for Chest X-ray Classificationin Low-Resource Clinical Settings.- Deep learning based Automatic detection of adequately positioned mammograms.- Can non-specialists provide high quality Gold standard labels in challenging modalities.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 280 pp. Englisch.