The growing use of the Internet in every life area creates an emerging need to provide information security (IS), and numerous classification algorithms approach this problem. This study provides a systematic literature review on the classification algorithms applications for information security on the ...
Classification problems are one of the most common scenarios we face in data science. This course will help you understand and apply common algorithms to make predictions and drive decision-making in business. Whether you’re an aspiring data scientist, studying analytics, or have a focus on busi...
ClassificationClassifier Output for Machine Learning ClassificationConclusionReferences#Introduction#Operational Perspective of WEKA#Opening WEKA#Weka Explorer Preprocess Panel#Weka Explorer Classify Panel#Prevalent WEKA Algorithms#J48 Decision Tree#K-Nearest Neighbors#Logistic Regression#Nave Bayes#Support Vector ...
The resulting robot learns to approach, recognize, and grasp objects on a floor effectively and efficiently. Experimental results show that highly accurate classification procedures can be learned without sacrificing efficiency in the case of both synthetic and real domains....
Library of Congress Cataloging-in-Publication Data Zhu, Zhechen. Automatic modulation classification : principles, algorithms, and applications / Zhechen Zhu and Asoke K. Nandi. pages cm Includes bibliographical references and index. ISBN 978-1-118-90649-1 (cloth) ...
Classification of a class ofA3MDSMDScode and applications in secret-sharing schemes Bandana Pandeyand Prabal Paul Vol. 16, No. 07 Co-normal products and modular products of soft graphs Bobin George, Jinta Jose, and Rajesh K. Thumbakara ...
10.1 Introduction The primary purpose of modulation classification in military scenarios is to ascertain information about an adversary by intercepting radiated energy. The detection and subsequent identification of the signal modulation have three possible uses. First, the knowledge of the modulation scheme...
6.2 图像分类(Image classification) 6.2.1 基于特征的方法(Feature-based methods) 6.2.2 深层网络(Deep networks) 6.2.3 应用:视觉相似度搜索(Application: Visual similarity search) 6.2.4 人脸识别(Face recognition) 6.3 物体检测(Object detection) 6.3.1 人脸检测(Face detection) 6.3.2 行人检测(Pedestrian...
E.g., GPU (Graphical processing unit) in the case of Deep Learning algorithms in object recognition, image classification, etc. The implementation's performance is measured by connection per the second number (cps), i.e., the number of data chunks transported through the neural network's edge...
2.A Survey on Self-supervised Learning: Algorithms, Applications, and Future Trends.Jie Gui, Tuo Chen, Jing V. R. de Sa, “Learning classification with unlabeled data,” inNeural Inf. Process. Syst., pp. 112–119, 1994 Devlin, Jacob et al. “BERT:Pre-trainingof Deep Bidirectional Transf...