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Evidence-Based Infectious Diseases
This major text discusses evidence based practice in the principal infectious disease groups. The introduction covers the methodology of systematic reviews in the context of infectious disease, and this is followed by contributions from the leading world experts on the current evidence for best treatments. The book is accompanied by a searchable CDRom of the full text and it will be kept up to date with regular updates of the evidence on its own free access website - www.evidbasedinfectiousdisease.com
Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013
The computer recognition systems are nowadays one of the most promising directions in artificial intelligence. This book is the most comprehensive study of this field. It contains a collection of 86 carefully selected articles contributed by experts of pattern recognition. It reports on current research with respect to both methodology and applications. In particular, it includes the following sections: Biometrics Data Stream Classification and Big Data Analytics Features, learning, and classifiers Image processing and computer vision Medical applications Miscellaneous applications Pattern recognition and image processing in robotics Speech and word recognition This book is a great reference tool for scientists who deal with the problems of designing computer pattern recognition systems. Its target readers can be the as well researchers as students of computer science, artificial intelligence or robotics.
Evidence-Based Infectious Diseases, with CD-ROM
This major text discusses evidence based practice in the principal infectious disease groups. The introduction covers the methodology of systematic reviews in the context of infectious disease, and this is followed by contributions from the leading world experts on the current evidence for best treatments. The book is accompanied by a searchable CDRom of the full text and it will be kept up to date with regular updates of the evidence on its own free access website - www.evidbasedinfectiousdisease.com
Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions
The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.
Neural Information Processing
The three-volume set of LNCS 12532, 12533, and 12534 constitutes the proceedings of the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020. Due to COVID-19 pandemic the conference was held virtually. The 187 full papers presented were carefully reviewed and selected from 618 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The third volume, LNCS 12534, is organized in topical sections on biomedical information; neural data analysis; neural network models; recommender systems; time series analysis.
Computer Information Systems and Industrial Management
This book constitutes the proceedings of the 13th IFIP TC 8 International Conference on Computer Information Systems and Industrial Management, CISIM 2014, held in Ho Chi Minh City, Vietnam, in November 2014. The 60 paper presented in this volume were carefully reviewed and selected from 98 submissions. They are organized in topical sections named: algorithms; biometrics and biometrics applications; data analysis and information retrieval; industrial management and other applications; modelling and optimization; networking; pattern recognition and image processing; and various aspects of computer security.
Machine Learning and Knowledge Discovery in Databases
The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022. The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions. The volumes are organized in topical sections as follows: Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge grap...
Neural Information Processing
The three-volume set of LNCS 11953, 11954, and 11955 constitutes the proceedings of the 26th International Conference on Neural Information Processing, ICONIP 2019, held in Sydney, Australia, in December 2019. The 173 full papers presented were carefully reviewed and selected from 645 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The second volume, LNCS 11954, is organized in topical sections on image processing by neural techniques; learning from incomplete data; model compression and optimisation; neural learning models; neural network applications; and social network computing.
Machine Learning and Knowledge Discovery in Databases: Research Track
The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023. The 196 papers were selected from the 829 submissions for the Research Track, and 58 papers were selected from the 239 submissions for the Applied Data Science Track. The volumes are organized in topical sections as follows: Part I: Active Learning; Adversarial Machine Learning; Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering. Part II: Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models;...
