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A Guide to Convolutional Neural Networks for Computer Vision
Computer vision has become increasingly important and effective in recent years due to its wide-ranging applications in areas as diverse as smart surveillance and monitoring, health and medicine, sports and recreation, robotics, drones, and self-driving cars. Visual recognition tasks, such as image classification, localization, and detection, are the core building blocks of many of these applications, and recent developments in Convolutional Neural Networks (CNNs) have led to outstanding performance in these state-of-the-art visual recognition tasks and systems. As a result, CNNs now form the crux of deep learning algorithms in computer vision. This self-contained guide will benefit those wh...
Robust Speech Recognition of Uncertain or Missing Data
Automatic speech recognition suffers from a lack of robustness with respect to noise, reverberation and interfering speech. The growing field of speech recognition in the presence of missing or uncertain input data seeks to ameliorate those problems by using not only a preprocessed speech signal but also an estimate of its reliability to selectively focus on those segments and features that are most reliable for recognition. This book presents the state of the art in recognition in the presence of uncertainty, offering examples that utilize uncertainty information for noise robustness, reverberation robustness, simultaneous recognition of multiple speech signals, and audiovisual speech recog...
Handbook of Deep Learning Applications
This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.
Face Recognition
Pattern recognition has gained significant attention due to the rapid explosion of internet- and mobile-based applications. Among the various pattern recognition applications, face recognition is always being the center of attraction. With so much of unlabeled face images being captured and made available on internet (particularly on social media), conventional supervised means of classifying face images become challenging. This clearly warrants for semi-supervised classification and subspace projection. Another important concern in face recognition system is the proper and stringent evaluation of its capability. This book is edited keeping all these factors in mind. This book is composed of five chapters covering introduction, overview, semi-supervised classification, subspace projection, and evaluation techniques.
Introduction to Combinatorial Designs, Second Edition
This new edition presents a comprehensive look at combinatorial designs. It coversclassical designs such as Latin squares, balanced incomplete block designs, and finite projective and affine planes as well as more contemporary designs that include one-factorizations, Room squares, tournament designs, and nested designs. The book featuresapplications in cryptography, computer science, experimental design, communications theory, and more. With every topic, it includes instructive examples and theorems. The text also provides exercises in each section, select answers in the back of the book, and more complete solutions on the author's website.
Computer Architecture '98
The third in the series of the Australasian Computer Architecture Conferences, ACAC98 was held in Perth, Australia, on the 2nd & 3rd of February 1998. This years submissions saw papers coming from Australia, Austria, China, Germany, Japan, New Zealand, Portugal, Singapore, Taiwan, and the United States, all presenting both novel as well as conventional architectural ideas. The 20 papers presented in this volume also cover the vital area of connection between processors - from geographically separated to closely coupled systems.
IEEE First ICA3PP
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Indigenous Grammar Across Cultures
This book deals with various «indigenous» traditions of grammatical thought across the globe. Its main perspective is a cross-cultural sociolinguistic and anthropological linguistic account of «Indigenous Grammar». The concept (relating to Bruno Liebich's term 'Einheimische Grammatik') is taken in its widest sense here to account for a continua of forms and ways of language-oriented research, various degrees of systematic reflection on language structure and use, the culture-specific ingredients of different grammatical «schools», linguistic and folk-linguistic speculation, language awareness, linguistic ideologies and similar endeavours. Some assumptions underlying the central hypotheses of this book are: - Linguistics, every grammatical description, has a strong cultural binding. - It is worthwhile to describe the culturally bound differences in a systematic fashion. - There are indigenous grammars and grammarians of entirely different denominations than what Western linguists are accustomed to dealing with. - A heuristic continua of indigenous grammar can be set up which is worth being studied by linguists in a cross-cultural comparative fashion.
