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1. |
Record Nr. |
UNISA996466031503316 |
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Titolo |
Machine Learning in Medical Imaging [[electronic resource] ] : 4th International Workshop, MLMI 2013, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013, Proceedings / / edited by Guorong Wu, Daoqiang Zhang, Dinggang Shen, Pingkun Yan, Kenji Suzuki, Fei Wang |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2013 |
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ISBN |
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Edizione |
[1st ed. 2013.] |
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Descrizione fisica |
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1 online resource (XII, 262 p. 94 illus.) |
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Collana |
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Image Processing, Computer Vision, Pattern Recognition, and Graphics ; ; 8184 |
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Disciplina |
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Soggetti |
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Optical data processing |
Pattern recognition |
Artificial intelligence |
Database management |
Computer graphics |
Image Processing and Computer Vision |
Pattern Recognition |
Artificial Intelligence |
Computer Imaging, Vision, Pattern Recognition and Graphics |
Database Management |
Computer Graphics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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Nota di contenuto |
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Unsupervised Deep Learning for Hippocampus Segmentation in 7.0 Tesla MR Images -- Integrating Multiple Network Properties for MCI Identification -- Learning-Boosted Label Fusion for Multi-atlas Auto-Segmentation -- Volumetric Segmentation of Key Fetal Brain Structures in 3D Ultrasound -- Sparse Classification with MRI Based Markers for Neuromuscular Disease Categorization -- Fully Automatic Detection of the Carotid Artery from Volumetric Ultrasound Images Using |
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Anatomical Position-Dependent LBP Features -- A Transfer-Learning Approach to Image Segmentation Across Scanners by Maximizing Distribution Similarity -- A New Algorithm of Electronic Cleansing for Weak Faecal-Tagging CT Colonography -- A Unified Approach to Shape Model Fitting and Non-rigid Registration -- A Bayesian Algorithm for Image-Based Time-to-Event Prediction -- Patient-Specific Manifold Embedding of Multispectral Images Using Kernel Combinations -- fMRI Analysis with Sparse Weisfeiler-Lehman Graph Statistics -- Patch-Based Segmentation without Registration: Application to Knee MRI -- Flow-Based Correspondence Matching in Stereovision -- Thickness NETwork (ThickNet) Features for the Detection of Prodromal AD -- Metric Space Structures for Computational Anatomy -- Discriminative Group Sparse Representation for Mild Cognitive Impairment Classification -- Temporally Dynamic Resting-State Functional Connectivity Networks for Early MCI Identification -- An Improved Optimization Method for the Relevance Voxel Machine -- Disentanglement of Session and Plasticity Effects in Longitudinal fMRI Studies -- Identification of Alzheimer’s Disease Using Incomplete Multimodal Dataset via Matrix Shrinkage and Completion -- On Feature Relevance in Image-Based Prediction Models: An Empirical Study -- Decision Forests with Spatio-Temporal Features for Graph-Based Tumor Segmentation in 4D Lung CT -- Improving Probabilistic Image Registration via Reinforcement Learning and Uncertainty Evaluation -- HEp-2 Cell Image Classification: A Comparative Analysis -- A 2.5D Colon Wall Flattening Model for CT-Based Virtual Colonoscopy -- Augmenting Auto-context with Global Geometric Features for Spinal Cord Segmentation -- Large-Scale Manifold Learning Using an Adaptive Sparse Neighbor Selection Approach for Brain Tumor Progression Prediction -- Ensemble Universum SVM Learning for Multimodal Classification of Alzheimer’s Disease -- Joint Sparse Coding Spatial Pyramid Matching for Classification of Color Blood Cell Image -- Multi-task Sparse Classifier for Diagnosis of MCI Conversion to AD with Longitudinal MR Images -- Sparse Multimodal Manifold-Regularized Transfer Learning for MCI Conversion Prediction. |
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Sommario/riassunto |
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This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Medical Imaging, MLMI 2013, held in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013, in Nagoya, Japan, in September 2013. The 32 contributions included in this volume were carefully reviewed and selected from 57 submissions. They focus on major trends and challenges in the area of machine learning in medical imaging and aim to identify new cutting-edge techniques and their use in medical imaging. |
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2. |
Record Nr. |
UNINA9910131387603321 |
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Autore |
Gouyon Marie |
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Titolo |
Les femmes dans la création audiovisuelle et de spectacle vivant : Les auteurs de la SACD percevant des droits en 2011 / / Marie Gouyon |
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Pubbl/distr/stampa |
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Paris, : Département des études, de la prospective et des statistiques, 2014 |
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ISBN |
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Descrizione fisica |
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1 online resource (16 p.) |
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Soggetti |
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Arts & Humanities |
Business |
emploi culturel |
féminisation |
spectacle |
SACD |
INSEE |
inégalités |
cultural employment |
feminization |
INSEE (National Institute of statistics and economic studies) |
performing art |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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En 2011, les femmes représentent 29 % des auteurs de la SACD et reçoivent 24 % des droits versés. Une femme perçoit ainsi, en 2011, un revenu moyen inférieur de 24 % à celui d’un homme. Les écarts de droits versés entre femmes et hommes trouvent plusieurs éléments d’explication : les femmes participent à moins d’œuvres que les hommes, en particulier dans le cinéma, le théâtre et les arts de la rue. Elles n’exercent pas non plus les mêmes fonctions, et sont ainsi plus souvent auteurs de texte ou chorégraphes que réalisatrices ou compositrices. À discipline et fonction égales, les écarts de rémunération sont |
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pratiquement inexistants dans la radio et la télévision, mais subsistent dans le cinéma et le spectacle vivant : ces écarts persistants peuvent être liés à d’autres facteurs comme, par exemple, une fréquentation des spectacles ou une programmation des œuvres moins importante, dans des lieux de représentation ou sur des canaux de diffusion différents et à des horaires moins favorables. In 2011, women represented 29% of SACD authors and received 24% of the royalties paid. As a result, in 2011, a woman received an average income 24% less than that for a man. The differences in royalties between men and women can be explained in several ways: women participate in fewer works than men, in particular in the cinema, theatre and street arts. Neither do they perform the same functions, and so are more often text authors or choreographers than directors or composers. For the same discipline and function the differences in remuneration are practically non-existent in radio and television, but live on in cinema and live shows: these persistent differences can be linked to other factors, such as, for example, lower audience numbers or programming of works, in different performance venues or on different distribution channels and at less favourable times. |
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