GB/T 25724-2010 English Translation of Chinese Standard PDF Download

Author: https://www.codeofchina.com
Publisher: https://www.codeofchina.com
ISBN:
Category : Architecture
Languages : en
Pages : 221

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Book Description
This standard specifies technical requirements of surveillance digital video and audio coding and decoding in the field of safety protection. This standard is applicable to real-time compression, transmission, broadcast, storage and other video and audio business in the field of safety protection, which may be used in other video and audio coding and decoding fields for reference.

Author: Matthew Moocarme
Publisher: Packt Publishing Ltd
ISBN: 1800200226
Category : Computers
Languages : en
Pages : 601

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Book Description
Get started with TensorFlow fundamentals to build and train deep learning models with real-world data, practical exercises, and challenging activities Key FeaturesUnderstand the fundamentals of tensors, neural networks, and deep learningDiscover how to implement and fine-tune deep learning models for real-world datasetsBuild your experience and confidence with hands-on exercises and activitiesBook Description Getting to grips with tensors, deep learning, and neural networks can be intimidating and confusing for anyone, no matter their experience level. The breadth of information out there, often written at a very high level and aimed at advanced practitioners, can make getting started even more challenging. If this sounds familiar to you, The TensorFlow Workshop is here to help. Combining clear explanations, realistic examples, and plenty of hands-on practice, it'll quickly get you up and running. You'll start off with the basics – learning how to load data into TensorFlow, perform tensor operations, and utilize common optimizers and activation functions. As you progress, you'll experiment with different TensorFlow development tools, including TensorBoard, TensorFlow Hub, and Google Colab, before moving on to solve regression and classification problems with sequential models. Building on this solid foundation, you'll learn how to tune models and work with different types of neural network, getting hands-on with real-world deep learning applications such as text encoding, temperature forecasting, image augmentation, and audio processing. By the end of this deep learning book, you'll have the skills, knowledge, and confidence to tackle your own ambitious deep learning projects with TensorFlow. What you will learnGet to grips with TensorFlow's mathematical operationsPre-process a wide variety of tabular, sequential, and image dataUnderstand the purpose and usage of different deep learning layersPerform hyperparameter-tuning to prevent overfitting of training dataUse pre-trained models to speed up the development of learning modelsGenerate new data based on existing patterns using generative modelsWho this book is for This TensorFlow book is for anyone who wants to develop their understanding of deep learning and get started building neural networks with TensorFlow. Basic knowledge of Python programming and its libraries, as well as a general understanding of the fundamentals of data science and machine learning, will help you grasp the topics covered in this book more easily.

Author: Sebastiano Battiato
Publisher: Springer
ISBN: 3319685481
Category : Computers
Languages : en
Pages : 814

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Book Description
The two-volume set LNCS 10484 and 10485 constitutes the refereed proceedings of the 19th International Conference on Image Analysis and Processing, ICIAP 2017, held in Catania, Italy, in September 2017. The 138 papers presented were carefully reviewed and selected from 229 submissions. The papers cover both classic and the most recent trends in image processing, computer vision, and pattern recognition, addressing both theoretical and applicative aspects. They are organized in the following topical sections: video analysis and understanding; pattern recognition and machine learning; multiview geometry and 3D computer vision; image analysis, detection and recognition; multimedia; biomedical and assistive technology; information forensics and security; imaging for cultural heritage and archaeology; and imaging solutions for improving the quality of life.

Author: Jolita Ralyté
Publisher: Springer Nature
ISBN: 3031179951
Category : Computers
Languages : en
Pages : 446

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Book Description
This book constitutes the refereed proceedings of the 41st International Conference on Conceptual Modeling, ER 2022, held in Hyderabad, India, in October 2022. The 19 full and 11 short papers were carefully reviewed and selected from 82 submissions. The papers are organzed in the following topical sections: ​foundations of conceptual modeling; ontologies and their applications; applications of conceptual modeling; data modeling and analysis; business process; quality and performance; security, privacy and risk management; goals and requirements.

Author: Jinho Kim
Publisher: Springer
ISBN: 331957454X
Category : Computers
Languages : en
Pages : 866

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Book Description
This two-volume set, LNAI 10234 and 10235, constitutes the thoroughly refereed proceedings of the 21st Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2017, held in Jeju, South Korea, in May 2017. The 129 full papers were carefully reviewed and selected from 458 submissions. They are organized in topical sections named: classification and deep learning; social network and graph mining; privacy-preserving mining and security/risk applications; spatio-temporal and sequential data mining; clustering and anomaly detection; recommender system; feature selection; text and opinion mining; clustering and matrix factorization; dynamic, stream data mining; novel models and algorithms; behavioral data mining; graph clustering and community detection; dimensionality reduction.

Author: Sridhar Alla
Publisher: Apress
ISBN: 1484251776
Category : Computers
Languages : en
Pages : 427

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Book Description
Utilize this easy-to-follow beginner's guide to understand how deep learning can be applied to the task of anomaly detection. Using Keras and PyTorch in Python, the book focuses on how various deep learning models can be applied to semi-supervised and unsupervised anomaly detection tasks. This book begins with an explanation of what anomaly detection is, what it is used for, and its importance. After covering statistical and traditional machine learning methods for anomaly detection using Scikit-Learn in Python, the book then provides an introduction to deep learning with details on how to build and train a deep learning model in both Keras and PyTorch before shifting the focus to applications of the following deep learning models to anomaly detection: various types of Autoencoders, Restricted Boltzmann Machines, RNNs & LSTMs, and Temporal Convolutional Networks. The book explores unsupervised and semi-supervised anomaly detection along with the basics of time series-based anomaly detection. By the end of the book you will have a thorough understanding of the basic task of anomaly detection as well as an assortment of methods to approach anomaly detection, ranging from traditional methods to deep learning. Additionally, you are introduced to Scikit-Learn and are able to create deep learning models in Keras and PyTorch. What You Will LearnUnderstand what anomaly detection is and why it is important in today's world Become familiar with statistical and traditional machine learning approaches to anomaly detection using Scikit-Learn Know the basics of deep learning in Python using Keras and PyTorch Be aware of basic data science concepts for measuring a model's performance: understand what AUC is, what precision and recall mean, and more Apply deep learning to semi-supervised and unsupervised anomaly detection Who This Book Is For Data scientists and machine learning engineers interested in learning the basics of deep learning applications in anomaly detection

Author: Susan Kahler
Publisher:
ISBN: 9781952365041
Category : Computers
Languages : en
Pages : 112

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Book Description
Computer vision is a field of artificial intelligence that trains computers to interpret and understand the visual world. In recent years, computer vision has begun to rival and even surpass human visual abilities in many areas. SAS offers many different solutions to train computers to "see" by identifying and classifying objects, and several groundbreaking papers have been written to demonstrate these techniques. The papers included in this special collection demonstrate how the latest computer vision tools and techniques can be used to solve a variety of business problems.

Author: Amit Kumar Singh
Publisher: Springer
ISBN: 303015887X
Category : Computers
Languages : en
Pages : 798

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Book Description
This handbook is organized under three major parts. The first part of this handbook deals with multimedia security for emerging applications. The chapters include basic concepts of multimedia tools and applications, biological and behavioral biometrics, effective multimedia encryption and secure watermarking techniques for emerging applications, an adaptive face identification approach for android mobile devices, and multimedia using chaotic and perceptual hashing function. The second part of this handbook focuses on multimedia processing for various potential applications. The chapter includes a detail survey of image processing based automated glaucoma detection techniques and role of de-noising, recent study of dictionary learning based image reconstruction techniques for analyzing the big medical data, brief introduction of quantum image processing and it applications, a segmentation-less efficient Alzheimer detection approach, object recognition, image enhancements and de-noising techniques for emerging applications, improved performance of image compression approach, and automated detection of eye related diseases using digital image processing. The third part of this handbook introduces multimedia applications. The chapter includes the extensive survey on the role of multimedia in medicine and multimedia forensics classification, a finger based authentication system for e-health security, analysis of recently developed deep learning techniques for emotion and activity recognition. Further, the book introduce a case study on change of ECG according to time for user identification, role of multimedia in big data, cloud computing, the Internet of things (IoT) and blockchain environment in detail for real life applications. This handbook targets researchers, policy makers, programmers and industry professionals in creating new knowledge for developing efficient techniques/framework for multimedia applications. Advanced level students studying computer science, specifically security and multimedia will find this book useful as a reference.

Author: Francesco Camastra
Publisher: Springer
ISBN: 144716735X
Category : Computers
Languages : en
Pages : 564

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Book Description
This second edition focuses on audio, image and video data, the three main types of input that machines deal with when interacting with the real world. A set of appendices provides the reader with self-contained introductions to the mathematical background necessary to read the book. Divided into three main parts, From Perception to Computation introduces methodologies aimed at representing the data in forms suitable for computer processing, especially when it comes to audio and images. Whilst the second part, Machine Learning includes an extensive overview of statistical techniques aimed at addressing three main problems, namely classification (automatically assigning a data sample to one of the classes belonging to a predefined set), clustering (automatically grouping data samples according to the similarity of their properties) and sequence analysis (automatically mapping a sequence of observations into a sequence of human-understandable symbols). The third part Applications shows how the abstract problems defined in the second part underlie technologies capable to perform complex tasks such as the recognition of hand gestures or the transcription of handwritten data. Machine Learning for Audio, Image and Video Analysis is suitable for students to acquire a solid background in machine learning as well as for practitioners to deepen their knowledge of the state-of-the-art. All application chapters are based on publicly available data and free software packages, thus allowing readers to replicate the experiments.

Author: Vittorio Murino
Publisher: Academic Press
ISBN: 0128092807
Category : Computers
Languages : en
Pages : 440

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Book Description
Group and Crowd Behavior for Computer Vision provides a multidisciplinary perspective on how to solve the problem of group and crowd analysis and modeling, combining insights from the social sciences with technological ideas in computer vision and pattern recognition. The book answers many unresolved issues in group and crowd behavior, with Part One providing an introduction to the problems of analyzing groups and crowds that stresses that they should not be considered as completely diverse entities, but as an aggregation of people. Part Two focuses on features and representations with the aim of recognizing the presence of groups and crowds in image and video data. It discusses low level processing methods to individuate when and where a group or crowd is placed in the scene, spanning from the use of people detectors toward more ad-hoc strategies to individuate group and crowd formations. Part Three discusses methods for analyzing the behavior of groups and the crowd once they have been detected, showing how to extract semantic information, predicting/tracking the movement of a group, the formation or disaggregation of a group/crowd and the identification of different kinds of groups/crowds depending on their behavior. The final section focuses on identifying and promoting datasets for group/crowd analysis and modeling, presenting and discussing metrics for evaluating the pros and cons of the various models and methods. This book gives computer vision researcher techniques for segmentation and grouping, tracking and reasoning for solving group and crowd modeling and analysis, as well as more general problems in computer vision and machine learning. - Presents the first book to cover the topic of modeling and analysis of groups in computer vision - Discusses the topics of group and crowd modeling from a cross-disciplinary perspective, using social science anthropological theories translated into computer vision algorithms - Focuses on group and crowd analysis metrics - Discusses real industrial systems dealing with the problem of analyzing groups and crowds