Machine Learning Techniques for Gait Biometric Recognition: Using the Ground Reaction Force, Mason James Eric, Traore Issa, Woungang Isaac
Автор: Somnath Dey, Debasis Samanta Название: Unimodal and Multimodal Biometric Data Indexing ISBN: 1614517452 ISBN-13(EAN): 9781614517450 Издательство: Walter de Gruyter Цена: 13937.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This work is on biometric data indexing for large-scale identification systems with a focus on different biometrics data indexing methods. It provides state-of-the-art coverage including different biometric traits, together with the pros and cons for each. Discussion of different multimodal fusion strategies are also included.
Автор: Munish Kumar, Manish Kumar Jindal, Simpel Rani Jindal, R. K. Sharma, Anupam Garg Название: Feature Extraction and Classification Techniques for Text Recognition ISBN: 1799824063 ISBN-13(EAN): 9781799824060 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 38669.00 р. Наличие на складе: Нет в наличии.
Описание: Presents innovative research on the fusion and hybridization of various features and classifiers for document analysis and recognition. The book highlights a range of topics, including adaptive boosting, writer identification, and signature verification.
Описание: The artificial intelligence subset machine learning has become a popular technique in professional fields as many are finding new ways to apply this trending technology into their everyday practices. Two fields that have majorly benefited from this are pattern recognition and information security. The ability of these intelligent algorithms to learn complex patterns from data and attain new performance techniques has created a wide variety of uses and applications within the data security industry. There is a need for research on the specific uses machine learning methods have within these fields, along with future perspectives.
Machine Learning Techniques for Pattern Recognition and Information Security is a collection of innovative research on the current impact of machine learning methods within data security as well as its various applications and newfound challenges. While highlighting topics including anomaly detection systems, biometrics, and intrusion management, this book is ideally designed for industrial experts, researchers, IT professionals, network developers, policymakers, computer scientists, educators, and students seeking current research on implementing machine learning tactics to enhance the performance of information security.
Описание: The artificial intelligence subset machine learning has become a popular technique in professional fields as many are finding new ways to apply this trending technology into their everyday practices. Two fields that have majorly benefited from this are pattern recognition and information security. The ability of these intelligent algorithms to learn complex patterns from data and attain new performance techniques has created a wide variety of uses and applications within the data security industry. There is a need for research on the specific uses machine learning methods have within these fields, along with future perspectives.
Machine Learning Techniques for Pattern Recognition and Information Security is a collection of innovative research on the current impact of machine learning methods within data security as well as its various applications and newfound challenges. While highlighting topics including anomaly detection systems, biometrics, and intrusion management, this book is ideally designed for industrial experts, researchers, IT professionals, network developers, policymakers, computer scientists, educators, and students seeking current research on implementing machine learning tactics to enhance the performance of information security.
Описание: You will learn the principles of computer vision and deep learning, and understand various models and architectures with their pros and cons. You will learn how to use TensorFlow 2.x to build your own neural network model and apply it to various computer vision tasks such as image acquiring, processing, and analyzing.
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