Lexical Input Processing and Vocabulary Learning

• Author : Joe Barcroft
• Publisher : John Benjamins Publishing Company
• Release : 15 December 2015

This book focuses on theory, research, and practice related to lexical input processing (lex-IP), an exciting field exploring how learners allocate their limited processing resources when exposed to words and lexical phrases in the input. Unit 1 specifies parameters of lex-IP research among other levels of input processing as well as key components (form, meaning, mapping) and contexts (incidental/intentional) of vocabulary learning. Unit 2 highlights theoretical advances, such as the type of processing – resource allocation (TOPRA) model, consistent with research on

• Author : D.J. Hemanth,V. Vieira Estrela
• Publisher : IOS Press
• Release : 01 December 2017

Deep learning and image processing are two areas of great interest to academics and industry professionals alike. The areas of application of these two disciplines range widely, encompassing fields such as medicine, robotics, and security and surveillance. The aim of this book, ‘Deep Learning for Image Processing Applications’, is to offer concepts from these two areas in the same platform, and the book brings together the shared ideas of professionals from academia and research about problems and solutions relating to

• Author : Li Deng,Yang Liu
• Publisher : Springer
• Release : 23 May 2018

In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. This book reviews the state of the art of deep learning research and its successful applications to

• Author : Zhiyuan Liu,Yankai Lin,Maosong Sun
• Publisher : Springer Nature
• Release : 03 July 2020

This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools

• Author : Wan-Chi Siu,Lap-Pui Chau,Liang Wang,Tieniu Tang
• Publisher : CRC Press
• Release : 07 December 2018

Coupled with machine learning, the use of signal processing techniques for big data analysis, Internet of things, smart cities, security, and bio-informatics applications has witnessed explosive growth. This has been made possible via fast algorithms on data, speech, image, and video processing with advanced GPU technology. This book presents an up-to-date tutorial and overview on learning technologies such as random forests, sparsity, and low-rank matrix estimation and cutting-edge visual/signal processing techniques, including face recognition, Kalman filtering, and multirate DSP.

• Author : Manel Martínez-Ramón,Arjun Gupta,José Luis Rojo-Álvarez,Christos G. Christodoulou
• Publisher : Artech House
• Release : 30 April 2021

This practical resource provides an overview of machine learning (ML) approaches as applied to electromagnetics and antenna array processing. Detailed coverage of the main trends in ML, including uniform and random array processing (beamforming and detection of angle of arrival), antenna optimization, wave propagation, remote sensing, radar, and other aspects of electromagnetic design are explored. An introduction to machine learning principles and the most common machine learning architectures and algorithms used today in electromagnetics and other applications is presented, including

• Author : Lakhmi C. Jain,Roumen Kountchev,Yonghang Tai
• Publisher : Springer Nature
• Release : 29 August 2021

This book presents high-quality research in the field of 3D imaging technology. The second edition of International Conference on 3D Imaging Technology (3DDIT-MSP&DL) continues the good traditions already established by the first 3DIT conference (IC3DIT2019) to provide a wide scientific forum for researchers, academia and practitioners to exchange newest ideas and recent achievements in all aspects of image processing and analysis, together with their contemporary applications. The conference proceedings are published in 2 volumes. The main topics of the

• Author : Paul Azunre
• Publisher : Simon and Schuster
• Release : 31 August 2021

Transfer Learning for Natural Language Processing teaches you to create powerful NLP solutions quickly by building on existing pretrained models. This instantly useful book provides crystal-clear explanations of the concepts you need to grok transfer learning along with hands-on examples so you can practice your new skills immediately. As you go, you'll apply state-of-the-art transfer learning methods to create a spam email classifier, a fact checker, and more real-world applications.

• Author : Regina Ward-Snyder
• Publisher : Gale, Cengage Learning
• Release : 30 August 2018

Gale Researcher Guide for: Social Learning, Information Processing, and Evolutionary Theories of Development is selected from Gale's academic platform Gale Researcher. These study guides provide peer-reviewed articles that allow students early success in finding scholarly materials and to gain the confidence and vocabulary needed to pursue deeper research.

• Author : Ali N. Akansu,Sanjeev R. Kulkarni,Dmitry M. Malioutov
• Publisher : John Wiley & Sons
• Release : 21 April 2016

The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions,

• Author : Sunil Patel
• Publisher : BPB Publications
• Release : 13 January 2021

Learn how to redesign NLP applications from scratch. KEY FEATURES • Get familiar with the basics of any Machine Learning or Deep Learning application. • Understand how does preprocessing work in NLP pipeline. • Use simple PyTorch snippets to create basic building blocks of the network commonly used in NLP. • Learn how to build a complex NLP application. • Get familiar with the advanced embedding technique, Generative network, and Audio signal processing techniques. DESCRIPTION Natural language processing (NLP) is one of the areas where

• Author : Stefan Th. Gries,Dagmar Divjak
• Publisher : Walter de Gruyter
• Release : 31 August 2012

The volume contains a collection of studies on how the analysis of corpus and psycholinguistic data reveal how linguistic knowledge is affected by the frequency of linguistic elements/stimuli. The studies explore a wide range of phenomena , from phonological reduction processes and palatalization to morphological productivity, diachronic change, adjective preposition constructions, auxiliary omission, and multi-word units. The languages studied are Spanish and artificial languages, Russian, Dutch, and English. The sister volume focuses on language representation.

• Author : Saeid Sanei,Jonathon A. Chambers
• Publisher : John Wiley & Sons
• Release : 23 September 2021

EEG Signal Processing and Machine Learning Explore cutting edge techniques at the forefront of electroencephalogram research and artificial intelligence from leading voices in the field The newly revised Second Edition of EEG Signal Processing and Machine Learning delivers an inclusive and thorough exploration of new techniques and outcomes in electroencephalogram (EEG) research in the areas of analysis, processing, and decision making about a variety of brain states, abnormalities, and disorders using advanced signal processing and machine learning techniques. The book

• Author : Anonim
• Publisher : Elsevier
• Release : 08 November 2018

Processing, Analyzing and Learning of Images, Shapes, and Forms: Volume 19, Part One provides a comprehensive survey of the contemporary developments related to the analysis and learning of images, shapes and forms. It covers mathematical models as well as fast computational techniques, and includes new chapters on Alternating diffusion: a geometric approach for sensor fusion, Shape Correspondence and Functional Maps, Geometric models for perception-based image processing, Decomposition schemes for nonconvex composite minimization: theory and applications, Low rank matrix recovery: algorithms and

• Author : Krzysztof Wolk
• Publisher : CRC Press
• Release : 25 February 2019

This book reviews ways to improve statistical machine speech translation between Polish and English. Research has been conducted mostly on dictionary-based, rule-based, and syntax-based, machine translation techniques. Most popular methodologies and tools are not well-suited for the Polish language and therefore require adaptation, and language resources are lacking in parallel and monolingual data. The main objective of this volume to develop an automatic and robust Polish-to-English translation system to meet specific translation requirements and to develop bilingual textual resources by