Автор: Xiaofei Lu Название: Computational Methods for Corpus Annotation and Analysis ISBN: 9401786445 ISBN-13(EAN): 9789401786447 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book reviews computational tools for lexical, syntactic, semantic, pragmatic and discourse analysis, with instructions on how to obtain, install and use each tool. Covers studies using Natural Language Processing, and offers ideas for better integration.
Автор: Xiaofei Lu Название: Computational Methods for Corpus Annotation and Analysis ISBN: 9402407804 ISBN-13(EAN): 9789402407808 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book reviews computational tools for lexical, syntactic, semantic, pragmatic and discourse analysis, with instructions on how to obtain, install and use each tool. Covers studies using Natural Language Processing, and offers ideas for better integration.
Описание: This book presents a unique opportunity for constructing a consistent image of collaborative manual annotation for Natural Language Processing (NLP).
Автор: Dash Название: Language Corpora Annotation and Processing ISBN: 9811629625 ISBN-13(EAN): 9789811629624 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book addresses the research, analysis, and description of the methods and processes that are used in the annotation and processing of language corpora in advanced, semi-advanced, and non-advanced languages.
Автор: Dash Niladri Sekhar Название: Language Corpora Annotation and Processing ISBN: 9811629595 ISBN-13(EAN): 9789811629594 Издательство: Springer Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book addresses the research, analysis, and description of the methods and processes that are used in the annotation and processing of language corpora in advanced, semi-advanced, and non-advanced languages.
Автор: Nancy Ide; James Pustejovsky Название: Handbook of Linguistic Annotation ISBN: 9402414266 ISBN-13(EAN): 9789402414264 Издательство: Springer Рейтинг: Цена: 55901.00 р. Наличие на складе: Нет в наличии.
Описание: Part one of this book covers all phases of the linguistic annotation process, from annotation scheme design and choice of representation format through both the manual and automatic annotation process, evaluation, and iterative improvement of annotation accuracy.
Автор: Alexiei Dingli Название: Knowledge Annotation: Making Implicit Knowledge Explicit ISBN: 3642268196 ISBN-13(EAN): 9783642268199 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book defines modern annotation, and analyzes its significance for future evolutions of the web. The authors examine the use of Artificial Intelligence and redundance in annotation tasks, and predict the future form and function of annotation.
Описание: This book constitutes the refereed joint proceedings of the 7th Joint International Workshop on Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2018, and the Third International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2018, held in conjunction with the 21th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 9 full papers presented at CVII-STENT 2017 and the 12 full papers presented at LABELS 2017 were carefully reviewed and selected. The CVII-STENT papers feature the state of the art in imaging, treatment, and computer-assisted intervention in the field of endovascular interventions. The LABELS papers present a variety of approaches for dealing with few labels, from transfer learning to crowdsourcing.
Автор: Khalid Belhajjame; Ashish Gehani; Pinar Alper Название: Provenance and Annotation of Data and Processes ISBN: 3319983784 ISBN-13(EAN): 9783319983783 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 7th International Provenance and Annotation Workshop, IPAW 2018, held in London, UK, in July 2018.
The 12 revised full papers, 19 poster papers, and 2 demonstration papers presented were carefully reviewed and selected from 50 submissions. The papers feature a variety of provenance-related topics ranging from the capture and inference of provenance to its use and application.They are organized in topical sections on reproducibility; modeling, simulating and capturing provenance; PROV extensions; scientific workflows; applications; and system demonstrations.
Автор: Kiyong Lee Название: Annotation-Based Semantics for Space and Time in Language ISBN: 1108839592 ISBN-13(EAN): 9781108839594 Издательство: Cambridge Academ Рейтинг: Цена: 20592.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Space and time representation in language is important in linguistics and cognitive science research, as well as artificial intelligence applications like conversational robots and navigation systems. This book is the first for linguists and computer scientists that shows how to do model-theoretic semantics for temporal or spatial information in natural language, based on annotation structures. The book covers the entire cycle of developing a specification for annotation and the implementation of the model over the appropriate corpus for linguistic annotation. Its representation language is a type-theoretic, first-order logic in shallow semantics. Each interpretation model is delimited by a set of definitions of logical predicates used in semantic representations (e.g., past) or measuring expressions (e.g., counts or k). The counting function is then defined as a set and its cardinality, involving a universal quantification in a model. This definition then delineates a set of admissible models for interpretation.
Автор: Bertram Lud?scher; Beth Plale Название: Provenance and Annotation of Data and Processes ISBN: 3319164619 ISBN-13(EAN): 9783319164618 Издательство: Springer Рейтинг: Цена: 7826.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the revised selected papers of the 5th International Provenance and Annotation Workshop, IPAW 2014, held in Cologne, Germany in June 2014. The 14 long papers, 20 short papers and 4 extended abstracts presented were carefully reviewed and selected from 53 submissions.
Описание: iMIMIC 2020.- Assessing attribution maps for explaining CNN-based vertebral fracture classifiers.- Projective Latent Interventions for Understanding and Fine-tuning Classifiers.- Interpretable CNN Pruning for Preserving Scale-Covariant Features in Medical Imaging.- Improving the Performance and Explainability of Mammogram Classifiers with Local Annotations.- Improving Interpretability for Computer-aided Diagnosis tools on Whole Slide Imaging with Multiple Instance Learning and Gradient-based Explanations.- Explainable Disease Classification via weakly-supervised segmentation.- Reliable Saliency Maps for Weakly-Supervised Localization of Disease Patterns.- Explainability for regression CNN in fetal head circumference estimation from ultrasound images.- MIL3ID 2020.- Recovering the Imperfect: Cell Segmentation in the Presence of Dynamically Localized Proteins.- Semi-supervised Instance Segmentation with a Learned Shape Prior.- COMe-SEE: Cross-Modality Semantic Embedding Ensemble for Generalized Zero-Shot Diagnosis of Chest Radiographs.- Semi-supervised Machine Learning with MixMatch and Equivalence Classes.- Non-contrast CT Liver Segmentation using CycleGAN Data Augmentation from Contrast Enhanced CT.- Uncertainty Estimation in Medical Image Localization: Towards Robust Anterior Thalamus Targeting for Deep Brain Stimulation.- A Case Study of Transfer of Lesion-Knowledge.- Transfer Learning With Joint Optimization for Label-Efficient Medical Image Anomaly Detection.- Unsupervised Wasserstein Distance Guided Domain Adaptation for 3D Multi-Domain Liver Segmentation.- HydraMix-Net: A Deep Multi-task Semi-supervised Learning Approach for Cell Detection and Classification.- Semi-supervised classification of chest radiographs.- LABELS 2020.- Risk of training diagnostic algorithms on data with demographic bias.- Semi-Weakly Supervised Learning for Prostate Cancer Image Classification with Teacher-Student Deep Convolutional Networks.- Are pathologist-defined labels reproducible? Comparison of the TUPAC16 mitotic figure dataset with an alternative set of labels.- EasierPath: An Open-source Tool for Human-in-the-loop Deep Learning of Renal Pathology.- Imbalance-Effective Active Learning in Nucleus, Lymphocyte and Plasma Cell Detection.- Labeling of Multilingual Breast MRI Reports.- Predicting Scores of Medical Imaging Segmentation Methods with Meta-Learning.- Labelling imaging datasets on the basis of neuroradiology reports: a validation study.- Semi-Supervised Learning for Instrument Detection with a Class Imbalanced Dataset.- Paying Per-label Attention for Multi-label Extraction from Radiology Reports.
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