Machine Learning for Cup Coffee Quality Prediction from Green and Roasted Coffee Beans Features
Coffee is one of the main exported products of Colombia. It is grown in different regions throughout the territory and is recognized worldwide for its flavor and freshness. Its quality is evaluated by professional tasters, who taste the coffee drink obtai
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lied Computer Sciences in Engineering 7th Workshop on Engineering Applications, WEA 2020 Bogota, Colombia, October 7–9, 2020 Proceedings
Communications in Computer and Information Science Commenced Publication in 2007 Founding and Former Series Editors: Simone Diniz Junqueira Barbosa, Phoebe Chen, Alfredo Cuzzocrea, Xiaoyong Du, Orhun Kara, Ting Liu, Krishna M. Sivalingam, Dominik Ślęzak, Takashi Washio, Xiaokang Yang, and Junsong Yuan
Editorial Board Members Joaquim Filipe Polytechnic Institute of Setúbal, Setúbal, Portugal Ashish Ghosh Indian Statistical Institute, Kolkata, India Igor Kotenko St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, St. Petersburg, Russia Raquel Oliveira Prates Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil Lizhu Zhou Tsinghua University, Beijing, China
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More information about this series at http://www.springer.com/series/7899
Juan Carlos Figueroa-García Fabián Steven Garay-Rairán Germán Jairo Hernández-Pérez Yesid Díaz-Gutierrez (Eds.) •
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Applied Computer Sciences in Engineering 7th Workshop on Engineering Applications, WEA 2020 Bogota, Colombia, October 7–9, 2020 Proceedings
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Editors Juan Carlos Figueroa-García Universidad Distrital Francisco José de Caldas Bogotá, Colombia
Fabián Steven Garay-Rairán Infantry School of the National Colombian Army Bogotá, Colombia
Germán Jairo Hernández-Pérez National University of Colombia Bogotá, Colombia
Yesid Díaz-Gutierrez Corporación Unificada Nacional CUN Bogotá, Colombia
ISSN 1865-0929 ISSN 1865-0937 (electronic) Communications in Computer and Information Science ISBN 978-3-030-61833-9 ISBN 978-3-030-61834-6 (eBook) https://doi.org/10.1007/978-3-030-61834-6 © Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Spring
