Centre dedocumentation
scientifique

Atlas of global change risk of population and economic systems / Peijun Shi (2022)  

Public Titre : Atlas of global change risk of population and economic systems Type de document : Monographie Auteurs : Peijun Shi, Éditeur scientifique Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2022 Collection : IHDP/Future Earth-Integrated Risk Governance Project Series, ISSN 2363-4979 Importance : 278 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-981-1666933-- Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes IGN] cartographie des risques [Termes IGN] changement climatique [Termes IGN] économie internationale [Termes IGN] population [Termes IGN] risque naturel Résumé : (Editeur) This book is open access and illustrates the spatial distribution of the global change risk of population and economic systems with the maps of environment, global climate change, global population and economic systems, and global change risk. The risks of global change are mapped at 0.25 degree grid unit. The risk results and their contribution rates of the world at national level are unprecedentedly derived and ranked. The book can be a good reference for researchers and students in the field of global climate change and natural disaster risk management, as well as risk managers and enterpriser to understand the global change risk of population and economic systems. Note de contenu : Environments - Mapping Environments of the World / Peijun Shi, Jing’ai Wang, Ying Wang, Tian Liu Climate Changes - Mapping Temperature Changes / Xin Qi, Miaoni Gao, Tao Zhu, Siyu Li, Sicheng He, Jing Yang - Mapping Precipitation Changes / Xianghui Kong, Xiaoxin Wang, Huopo Chen, Aihui Wang, Dan Wan, Lianlian Xu et al. - Mapping Wind Speed Changes / Rui Mao, Cuicui Shi, Qi Zong, Xingya Feng, Yijie Sun, Yufei Wang et al. Population and Economic System Changes - Mapping Global Population Changes / Yujie Liu, Jie Chen - Mapping Global Population Exposure to Heatwaves / Qinmei Han, Wei Xu, Peijun Shi - Mapping Global Population Exposure to Rainstorms / Xinli Liao, Junlin Zhang, Wei Xu, Peijun Shi - Mapping Global GDP Distribution / Fubao Sun, Tingting Wang, Hong Wang - Mapping Global GDP Exposure to Drought / Fubao Sun, Tingting Wang, Hong Wang - Mapping Global Crop Distribution / Yaojie Yue, Peng Su, Yuan Gao, Puying Zhang, Ran Wang, Anyu Zhang et al. - Mapping Global Crop Exposure to Extremely High Temperature / Yaojie Yue, Peng Su, Yuan Gao, Puying Zhang, Ran Wang, Anyu Zhang et al. - Mapping Global Industrial Value Added / Wei Song, Huiyi Zhu, Han Li, Qian Xue, Yuanzhe Liu - Mapping Global Road Networks / Wenxiang Wu, Lingyun Hou Global Change Risks - Mapping Global Risk of Heatwave Mortality Under Climate Change / Qinmei Han, Weihang Liu, Wei Xu, Peijun Shi - Mapping Global Risk of River Flood Mortality / Junlin Zhang, Xinli Liao, Wei Xu - Mapping Global Risk of GDP Loss to River Floods / Junlin Zhang, Xinli Liao, Wei Xu - Mapping Global Risk of Crop Yield Under Climate Change / Weihang Liu, Shuo Chen, Qingyang Mu, Tao Ye, Peijun Shi Numéro de notice : 26789 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Monographie DOI : 10.1007/978-981-16-6691-9 En ligne : https://doi.org/10.1007/978-981-16-6691-9 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99926

A benchmark of named entity recognition approaches in historical documents : application to 19th century French directories / Nathalie Abadie (2022)  

Public Titre : A benchmark of named entity recognition approaches in historical documents : application to 19th century French directories Type de document : Article/Communication Auteurs : Nathalie Abadie , Auteur ; Edwin Carlinet, Auteur ; Joseph Chazalon, Auteur ; Bertrand Duménieu , Auteur Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2022 Collection : Lecture notes in Computer Science, ISSN 0302-9743 num. 13237 Projets : SODUCO / Perret, Julien Conférence : DAS 2022, 5th IAPR International Workshop on Document Analysis Systems 22/05/2022 25/05/2022 La Rochelle France Proceedings Springer Importance : pp 445 - 460 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] dix-neuvième siècle [Termes IGN] données d'entrainement (apprentissage automatique) [Termes IGN] exploration de texte [Termes IGN] objet géohistorique [Termes IGN] reconnaissance de noms [Termes IGN] traitement du langage naturel Résumé : (auteur) Named entity recognition (NER) is a necessary step in many pipelines targeting historical documents. Indeed, such natural language processing techniques identify which class each text token belongs to, e.g. “person name”, “location”, “number”. Introducing a new public dataset built from 19th century French directories, we first assess how noisy modern, off-the-shelf OCR are. Then, we compare modern CNN- and Transformer-based NER techniques which can be reasonably used in the context of historical document analysis. We measure their requirements in terms of training data, the effects of OCR noise on their performance, and show how Transformer-based NER can benefit from unsupervised pre-training and supervised fine-tuning on noisy data. Results can be reproduced using resources available at https://github.com/soduco/paper-ner-bench-das22 and https://zenodo.org/record/6394464. Numéro de notice : C2022-030 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers HAL Thématique : GEOMATIQUE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1007/978-3-031-06555-2_30 En ligne : http://dx.doi.org/10.1007/978-3-031-06555-2_30 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101088

Beyond 100: The Next Century in Geodesy / J. Freymueller (2022)  

Public Titre : Beyond 100: The Next Century in Geodesy : Proceedings of the IAG General Assembly, Montreal, Canada, July 8-18, 2019 Type de document : Actes de congrès Auteurs : J. Freymueller, Éditeur scientifique ; Laura Sánchez, Éditeur scientifique Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2022 Collection : International Association of Geodesy Symposia, ISSN 0939-9585 num. 152 Conférence : IAG 2019, General Assembly 08/07/2019 18/07/2019 Montreal Canada OA proceedings Importance : 663 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-031-09857-4 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie [Termes IGN] géodynamique [Termes IGN] hydrosphère [Termes IGN] marée terrestre [Termes IGN] modèle de géopotentiel [Termes IGN] positionnement par GNSS [Termes IGN] positionnement ponctuel précis [Termes IGN] rotation de la Terre [Termes IGN] système de référence géodésique Résumé : (éditeur) This open access book contains 30 peer-reviewed papers based on presentations at the 27th General Assembly of the International Union of Geodesy and Geophysics (IUGG). The meeting was held from July 8 to 18, 2019 in Montreal, Canada, with the theme being the celebration of the centennial of the establishment of the IUGG. The centennial was also a good opportunity to look forward to the next century, as reflected in the title of this volume. The papers in this volume represent a cross-section of present activity in geodesy, and highlight the future directions in the field as we begin the second century of the IUGG. During the meeting, the International Association of Geodesy (IAG) organized one Union Symposium, 6 IAG Symposia, 7 Joint Symposia with other associations, and 20 business meetings. In addition, IAG co-sponsored 8 Union Symposia and 15 Joint Symposia. In total, 3952 participants registered, 437 of them with IAG priority. In total, there were 234 symposia and 18 Workshops with 4580 presentations, of which 469 were in IAG-associated symposia. Note de contenu : I- Multi-Signal Positioning, Remote Sensing and Applications II- Monitoring and Understanding the Dynamic Earth with Geodetic Observations III- Geodesy for Atmospheric and Hydrospheric Climate Research (IAG, IAMAS, IACS, IAPSO) Numéro de notice : 24104 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Actes DOI : sans En ligne : https://link.springer.com/book/10.1007/978-3-031-09857-4?page=2#toc Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102748

Contient

• Estimation of Lesser Antilles vertical velocity fields using a GNSS-PPP software comparison / Pierre Sakic-Kieffer (2022)  

Machine Learning: The Basics / Alexander Jung (2022)  

Public Titre : Machine Learning: The Basics Type de document : Guide/Manuel Auteurs : Alexander Jung, Auteur Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2022 Importance : 280 p. Note générale : glossaire arXiv:1805.05052 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle [Termes IGN] apprentissage automatique [Termes IGN] apprentissage dirigé [Termes IGN] apprentissage non-dirigé [Termes IGN] apprentissage par renforcement [Termes IGN] données d'entrainement (apprentissage automatique) [Termes IGN] intelligence artificielle [Termes IGN] modèle numérique Résumé : (auteur) Machine learning (ML) has become a commodity in our every-day lives. We routinely ask ML empowered smartphones to suggest lovely food places or to guide us through a strange place. ML methods have also become standard tools in many fields of science and engineering. A plethora of ML applications transform human lives at unprecedented pace and scale. This book portrays ML as the combination of three basic components: data, model and loss. ML methods combine these three components within computationally efficient implementations of the basic scientific principle "trial and error". This principle consists of the continuous adaptation of a hypothesis about a phenomenon that generates data. ML methods use a hypothesis to compute predictions for future events. We believe that thinking about ML as combinations of three components given by data, model, and loss helps to navigate the steadily growing offer for ready-to-use ML methods. Our three-component picture of ML allows a unified treatment of a wide range of concepts and techniques which seem quite unrelated at first sight. The regularization effect of early stopping in iterative methods is due to the shrinking of the effective hypothesis space. Privacy-preserving ML is obtained by particular choices for the features of data points. Explainable ML methods are characterized by particular choices for the hypothesis space. To make good use of ML tools it is instrumental to understand its underlying principles at different levels of detail. On a lower level, this tutorial helps ML engineers to choose suitable methods for the application at hand. The book also offers a higher-level view on the implementation of ML methods which is typically required to manage a team of ML engineers and data scientists. Numéro de notice : 17721 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE/INFORMATIQUE Nature : Manuel de cours DOI : sans En ligne : https://arxiv.org/abs/1805.05052 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100081

Metalearning / Pavel Brazdil (2022)  

Public Titre : Metalearning : Applications to automated machine learning and data mining Type de document : Monographie Auteurs : Pavel Brazdil, Auteur ; Jan N. van Rijn, Auteur ; Carlos Soares, Auteur ; Joaquin Vanschoren, Auteur Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2022 Importance : 346 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-030-67024-5 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle [Termes IGN] algorithme d'apprentissage [Termes IGN] analyse de groupement [Termes IGN] apprentissage automatique [Termes IGN] chaîne de traitement [Termes IGN] échantillonnage [Termes IGN] modèle stochastique [Termes IGN] ontologie [Termes IGN] optimisation (mathématiques) [Termes IGN] régression [Termes IGN] science des données [Termes IGN] série temporelle Résumé : (éditeur) This open access book as one of the fastest-growing areas of research in machine learning, metalearning studies principled methods to obtain efficient models and solutions by adapting machine learning and data mining processes. This adaptation usually exploits information from past experience on other tasks and the adaptive processes can involve machine learning approaches. As a related area to metalearning and a hot topic currently, automated machine learning (AutoML) is concerned with automating the machine learning processes. Metalearning and AutoML can help AI learn to control the application of different learning methods and acquire new solutions faster without unnecessary interventions from the user. This book offers a comprehensive and thorough introduction to almost all aspects of metalearning and AutoML, covering the basic concepts and architecture, evaluation, datasets, hyperparameter optimization, ensembles and workflows, and also how this knowledge can be used to select, combine, compose, adapt and configure both algorithms and models to yield faster and better solutions to data mining and data science problems. It can thus help developers to develop systems that can improve themselves through experience. This book is a substantial update of the first edition published in 2009. It includes 18 chapters, more than twice as much as the previous version. This enabled the authors to cover the most relevant topics in more depth and incorporate the overview of recent research in the respective area. The book will be of interest to researchers and graduate students in the areas of machine learning, data mining, data science and artificial intelligence. ; Metalearning is the study of principled methods that exploit metaknowledge to obtain efficient models and solutions by adapting machine learning and data mining processes. While the variety of machine learning and data mining techniques now available can, in principle, provide good model solutions, a methodology is still needed to guide the search for the most appropriate model in an efficient way. Metalearning provides one such methodology that allows systems to become more effective through experience. This book discusses several approaches to obtaining knowledge concerning the performance of machine learning and data mining algorithms. It shows how this knowledge can be reused to select, combine, compose and adapt both algorithms and models to yield faster, more effective solutions to data mining problems. It can thus help developers improve their algorithms and also develop learning systems that can improve themselves. The book will be of interest to researchers and graduate students in the areas of machine learning, data mining and artificial intelligence. Note de contenu : 1- Basic concepts and architecture 2- Advanced techniques and methods 3- Organizing and Exploiting Metadata Numéro de notice : 28698 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/MATHEMATIQUE Nature : Monographie DOI : 10.1007/978-3-030-67024-5 En ligne : https://doi.org/10.1007/978-3-030-67024-5 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100469

Online segmentation of LiDAR sequences: dataset and algorithm / Romain Loiseau (2022)  

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Combining deep learning and mathematical morphology for historical map segmentation / Yizi Chen (2021)  

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Guide to Maritime Informatics, ch. Maritime Network Analysis: Connectivity and Spatial Distribution / César Ducruet (2021)  

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Polarimetric Synthetic Aperture Radar / Irena Hajnsek (2021)  

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Review of Reference Frame Representations for a Deformable Earth / Zuheir Altamimi (2021)  

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Advanced GNSS tropospheric products for monitoring severe weather events and climate, ch. 5. Use of GNSS Tropospheric Products for Climate Monitoring (Working Group 3) / Olivier Bock (2020)  

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Advanced GNSS tropospheric products for monitoring severe weather events and climate / Jonathan Jones (2020)  

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Advances in Intelligent Data Analysis XVIII : 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29 2020 / Michael R. Berthold (2020)  

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Ionospheric multi-spacecraft analysis tools / Malcolm Wray Dunlop (2020)  

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Knowledge graphs and big data processing / Valentina Janev (2020)  

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