Название: Handbook of Digital Face Manipulation and Detection: From DeepFakes to Morphing Attacks
Автор: Christian Rathgeb, Ruben Tolosana
Издательство: Springer
Серия: Advances in Computer Vision and Pattern Recognition
Год: 2022
Страниц: 481
Язык: английский
Формат: pdf (true)
Размер: 13.5 MB

This book provides the first comprehensive collection of studies dealing with the hot topic of digital face manipulation such as DeepFakes, Face Morphing, or Reenactment. It combines the research fields of biometrics and media forensics including contributions from academia and industry. Appealing to a broad readership, introductory chapters provide a comprehensive overview of the topic, which address readers wishing to gain a brief overview of the state-of-the-art. Subsequent chapters, which delve deeper into various research challenges, are oriented towards advanced readers. Moreover, the book provides a good starting point for young researchers as well as a reference guide pointing at further literature. Hence, the primary readership is academic institutions and industry currently involved in digital face manipulation and detection. The book could easily be used as a recommended text for courses in image processing, Machine Learning, media forensics, biometrics, and the general security area.

Название: Formal Methods in Computer Science
Автор: Jiacun Wang, William Tepfenhart
Издательство: CRC Press
Год: 2020
Страниц: 313
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Formal Methods in Computer Science gives students a comprehensive introduction to formal methods and their application in software and hardware specification and verification. The first part introduces some fundamentals in formal methods, including set theory, functions, finite state machines, and regular expressions. The second part focuses on logic, a powerful formal language in specifying systems properties. It covers propositional logic, predicate logic, temporal logic, and model checking. The third part presents Petri nets, the most popular formal language in system behavior modeling. In additional to regular Petri nets, this part also examines timed Petri nets and high-level Petri nets.

Название: Beginning Deep Learning with TensorFlow: Work with Keras, MNIST Data Sets, and Advanced Neural Networks
Автор: Liangqu Long, Xiangming Zeng
Издательство: Apress
Год: 2022
Страниц: 727
Язык: английский
Формат: pdf (true)
Размер: 19.4 MB

Incorporate deep learning into your development projects through hands-on coding and the latest versions of deep learning software, such as TensorFlow 2 and Keras. The materials used in this book are based on years of successful online education experience and feedback from thousands of online learners. You’ll start with an introduction to AI, where you’ll learn the history of neural networks and what sets deep learning apart from other varieties of machine learning. Discovery the variety of deep learning frameworks and set-up a deep learning development environment. Next, you’ll jump into simple classification programs for hand-writing analysis. Once you’ve tackled the basics of deep learning, you move on to TensorFlow 2 specifically.

Название: Machine Learning and Optimization Models for Optimization in Cloud
Автор: Punit Gupta, Mayank K. Goyal
Издательство: CRC Press
Год: 2022
Страниц: 219
Язык: английский
Формат: pdf (true)
Размер: 15.1 MB

Machine Learning and Models for Optimization in Cloud’s main aim is to meet the user requirement with high quality of service, least time for computation and high reliability. With increase in services migrating over cloud providers, the load over the cloud increases resulting in fault and various security failure in the system results in decreasing reliability. To fulfill this requirement cloud system uses intelligent metaheuristic and prediction algorithm to provide resources to the user in an efficient manner to manage the performance of the system and plan for upcoming requests. Intelligent algorithm helps the system to predict and find a suitable resource for a cloud environment in real time with least computational complexity taking into mind the system performance in under loaded and over loaded condition.

Название: Meta-heuristic Optimization Techniques: Applications in Engineering
Автор: Anuj K., Sangeeta Pant, Mangey Ram
Издательство: De Gruyter
Год: 2022
Страниц: 204
Язык: английский
Формат: pdf (true), epub
Размер: 14.1 MB

This book is motivated by the fact that meta-heuristic optimization techniques have become very popular among researchers and engineers over the last two decades. The widespread applicability of various optimization methods makes them a hot spot for researchers. A few years back one even can’t think that school of fish, genes, nature of bat or ant can be used to design optimization algorithms, but nature has the solution of every problem. Nature-inspired optimization algorithms usually attempt to find a good approximation to the solution of complex optimization problems of various fields of sciences, engineering, and industries. It is applicable in almost all spheres of human life for the purpose of optimization of various parameters. Whereas a heuristic algorithm discovers the optimal solution in the search space of an optimization problem by “trial and error” with a weak guarantee of success, a metaheuristic algorithm performs better than that.

Название: Computational Thinking: A Perspective on Computer Science
Автор: Zhiwei Xu, Jialin Zhang
Издательство: Springer
Год: 2021
Страниц: 338
Язык: английский
Формат: pdf (true)
Размер: 10.0 MB

This textbook is intended as a textbook for one-semester, introductory computer science courses aimed at undergraduate students from all disciplines. Self-contained and with no prerequisites, it focuses on elementary knowledge and thinking models. The content has been tested in university classrooms for over six years, and has been used in summer schools to train university and high-school teachers on teaching introductory computer science courses using computational thinking. The book’s structure encourages active, hands-on learning using the pedagogic tool Bloom's taxonomy to create computational solutions to over 200 problems of varying difficulty. Students solve problems using a combination of thought experiment, programming, and written methods. Only 300 lines of code in total are required to solve most programming problems in this book.

Название: Issues With Facial Recognition Technology
Автор: Warren Lambert
Издательство: Nova Science Publishers
Год: 2021
Страниц: 232
Язык: английский
Формат: pdf (true)
Размер: 11.7 MB

Automated facial recognition systems compare two or more images of faces to determine whether they represent the same individual. Facial recognition technology (FRT) falls within the larger categories of biometric technology used to varying degrees by the government and private entities to identify persons. This book deals with some of the issues concerning facial recognition technology. Biometric technology uses automated processes to identify an individual through unique physical characteristics, such a fingerprints, speech patterns, or facial features. FRT can perform several functions, with the most common being face identification - the comparison of an unknown person’s face against a gallery of known persons - and face verification—confirmation of someone’s claimed identity. When an image of an unknown person is compared to a database, the technology may determine that an image in the database is sufficiently similar to register as a likely match. One or more likely matches may be identified. If no images are found to be sufficiently similar, the system will return no matches. Face identification can be used for surveillance, to find a person of interest, or for the identification of subjects who are either unable or unwilling to respond.

Название: Personalized Machine Learning
Автор: Julian McAuley
Издательство: Cambridge University Press
Год: 2022
Страниц: 337
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Every day we interact with Machine Learning systems offering individualized predictions for our entertainment, social connections, purchases, or health. These involve several modalities of data, from sequences of clicks to text, images, and social interactions. This book introduces common principles and methods that underpin the design of personalized predictive models for a variety of settings and modalities. The book begins by revising 'traditional' Machine Learning models, focusing on adapting them to settings involving user data, then presents techniques based on advanced principles such as matrix factorization, deep learning, and generative modeling, and concludes with a detailed study of the consequences and risks of deploying personalized predictive systems. A series of case studies in domains ranging from e-commerce to health plus hands-on projects and code examples will give readers understanding and experience with large-scale real-world datasets and the ability to design models and systems for a wide range of applications.

Название: Machine Learning: Neural Networks, Decision Trees and Support Vector Machine with IBM SPSS Modeler
Автор: L. Marvin
Издательство: Lulu.com
Год: 2021
Страниц: 275
Язык: английский
Формат: epub
Размер: 13.0 MB

Machine Learning techniques are intended to extract the knowledge contained in the data through models and other appropriate techniques. Within Machine Learning techniques there are two fundamental types: supervised learning techniques and unsupervised learning techniques. Supervised learning techniques include all those that use a model in which there are dependent variables and independent variables. The purpose of these techniques is usually prediction or classification of both at the same time. Neural networks, decision trees, and SVM models are supervised learning machine learning techniques for prediction and classification. It is precisely these techniques that are developed in this book using IBM SPSS Modeler software.

Название: Animated Problem Solving: An Introduction to Program Design Using Video Game Development
Автор: Marco T. Morazan
Издательство: Springer
Серия: Texts in Computer Science
Год: 2022
Страниц: 688
Язык: английский
Формат: pdf (true)
Размер: 10.9 MB

This textbook is about systematic problem solving and systematic reasoning using type-driven design. There are two problem solving techniques that are emphasized throughout the book:divide and conqueranditerative refinement. Divide and conquer is the process by which a large problem is broken into two or more smaller problems that are easier to solve and then the solutions for the smaller pieces are combined to create an answer to the problem. Iterative refinement is the process by which a solution to a problem is gradually made better–like the drafts of an essay. Mastering these techniques are essential to becoming a good problem solver and programmer. In this textbook, all the solutions to problems are expressed as programs. It is important to be somewhat precise about what a program is. A program is much more than just code written using a programming language. Remember that a program is a solution to a problem. Therefore, a program has a design, code, examples of how it works, and tests. That is, it communicates how the problem is solved and illustrates that the solution works. If any of the mentioned components are missing, then we have an incomplete program.