"This book provides a comprehensive overview of the research on anomaly detection with respect to context and situational awareness that aim to get a better understanding of how context information influences anomaly detection. In each chapter, it identifies advanced anomaly detection and key assump
Applied cloud deep semantic recognition : advanced anomaly detection
โ Scribed by Rad, Paul; Roopaei, Mehdi
- Publisher
- Auerbach
- Year
- 2018
- Tongue
- English
- Leaves
- 203
- Edition
- 1st
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Table of Contents
Content: 1 Large-Scale Video Event Detection Using Deep Neural Networks 2 Leveraging Selectional Preferences for Anomaly Detection in Newswire Events 3 Abnormal Event Recognition in Crowd Environments 4 Cognitive Sensing: Adaptive Anomalies Detection with Deep Networks 5 Language-Guided Visual Recognition 6 Deep Learning for Font Recognition and Retrieval 7 A Distributed Secure Machine-Learning Cloud Architecture for Semantic Analysis 8 A Practical Look at Anomaly Detection Using Autoencoders with H2O and the R Programming Language
โฆ Subjects
Semantic computing.;Anomaly detection (Computer security);Invisible Web.
๐ SIMILAR VOLUMES
<p><span>Object detection is a basic visual identification problem in computer vision that has been explored extensively over the years. Visual object detection seeks to discover objects of specific target classes in a given image with pinpoint accuracy and apply a class label to each object instanc
<p><span>This beginner-oriented book will help you understand and perform anomaly detection by learning cutting-edge machine learning and deep learning techniques. This updated second edition focuses on supervised, semi-supervised, and unsupervised approaches to anomaly detection. Over the course of
This beginner-oriented book will help you understand and perform anomaly detection by learning cutting-edge machine learning and deep learning techniques. This updated second edition focuses on supervised, semi-supervised, and unsupervised approaches to anomaly detection. Over the course of the book
This beginner-oriented book will help you understand and perform anomaly detection by learning cutting-edge machine learning and deep learning techniques. This updated second edition focuses on supervised, semi-supervised, and unsupervised approaches to anomaly detection. Over the course of the book
Develop and optimize deep learning models with advanced architectures. This book teaches you the intricate details and subtleties of the algorithms that are at the core of convolutional neural networks. In<i>Advanced Applied Deep Learning</i>, you will study advanced topics on CNN and object detecti