Search results: Found 20

Listing 11 - 20 of 20 << page
of 2
>>
Sort by
The Ik language: Dictionary and grammar sketch

Author:
Book Series: African Language Grammars and Dictionaries ISBN: 9783944675954 9783944675961 9783944675688 Year: Pages: 569 DOI: 10.5281/zenodo.344792 Language: English
Publisher: Language Science Press
Subject: Linguistics
Added to DOAB on : 2017-06-29 11:02:01
License:

Loading...
Export citation

Choose an application

Abstract

This book is a dictionary and grammar sketch of Ik, one of the three Kuliak (Rub) languages spoken in the beautiful Karamoja region of northeastern Uganda. It is the lexicographic sequel to A grammar of Ik (Icé-tód): Northeast Uganda’s last thriving Kuliak language (Schrock 2014). The present volume includes an Ik-English dictionary with roughly 8,700 entries, followed by a reversed English-Ik index. These two main sections are then supplemented with an outline of Ik grammar that is comprehensive in its coverage of topics and written in a simple style, using standard linguistic terminology in a way that is accessible to interested non-linguists as well. This book may prove useful for language preservation and development among the Ik people, as a reference tool for non-Ik learners of the language, and as a source of data, not only for the comparative study of Kuliak but also the wider Afroasiatic and Nilo-Saharan language families.

Dictionary of the British English Spelling System

Author:
ISBN: 9781783741090 9781783741083 Year: Pages: 522 DOI: 10.11647/OBP.0053 Language: English
Publisher: Open Book Publishers
Subject: Linguistics
Added to DOAB on : 2015-06-10 13:31:46
License:

Loading...
Export citation

Choose an application

Abstract

This book will tell all you need to know about British English spelling. It’s a reference work intended for anyone interested in the English language, especially those who teach it, whatever the age or mother tongue of their students. It will be particularly useful to those wishing to produce well-designed materials for teaching initial literacy via phonics, for teaching English as a foreign or second language, and for teacher training.English spelling is notoriously complicated and difficult to learn; it is correctly described as much less regular and predictable than any other alphabetic orthography. However, there is more regularity in the English spelling system than is generally appreciated. This book provides, for the first time, a thorough account of the whole complex system. It does so by describing how phonemes relate to graphemes and vice versa. It enables searches for particular words, so that one can easily find, not the meanings or pronunciations of words, but the other words with which those with unusual phoneme-grapheme/grapheme-phoneme correspondences keep company.Other unique features of this book include teacher-friendly lists of correspondences and various regularities not described by previous authorities, for example the strong tendency for the letter-name vowel phonemes (the names of the letters ) to be spelt with those single letters in non-final syllables.

A dictionary and grammatical outline of Chakali

Author:
Book Series: African Language Grammars and Dictionaries ISBN: 9783944675916 9783944675923 9783946234937 Year: Pages: 491 DOI: 10.5281/zenodo.344813 Language: English
Publisher: Language Science Press
Subject: Linguistics
Added to DOAB on : 2017-06-29 11:02:00
License:

Loading...
Export citation

Choose an application

Abstract

This book is the first comprehensive monograph dedicated to Chakali, a Southwestern Grusi language spoken by less than 3500 people in northwest Ghana. The dictionary offers a consistent description of word meaning and provides the basis for future research in the linguistic area. It is also designed to provide an inventory of correspondence with English usage in a reversal index. The concepts used in the dictionary are explained in a grammar outline, which is of interest to specialists in Gur and Grusi linguistics, as well as any language researchers working in this part of the world.

Classic Concepts in Anthropology

Authors: --- ---
ISBN: 9780990505082 Year: Language: English
Publisher: HAU Books Grant: Knowledge Unlatched - 101680
Subject: Anthropology
Added to DOAB on : 2018-07-10 11:01:02
License:

Loading...
Export citation

Choose an application

Abstract

The late anthropologist Valerio Valeri (1944–98) was best known for his substantial writings on societies of Polynesia and eastern Indonesia. This volume, however, presents a lesser-known side of Valeri’s genius through a dazzlingly erudite set of comparative essays on core topics in the history of anthropological theory. Offering masterly discussions of anthropological thought about ritual, fetishism, cosmogonic myth, belief, caste, kingship, mourning, play, feasting, ceremony, and cultural relativism, Classic Concepts in Anthropology, presented here with a critical foreword by Rupert Stasch and Giovanni da Col, will be an eye-opening, essential resource for students and researchers not only in anthropology but throughout the humanities.

Das Russisch-Deutsche Woerterbuch von Iwan Pawlowsky

Author:
Book Series: Slavistische Beitraege ISBN: 9783876908540 Year: Pages: 208 DOI: 10.3726/b12700 Language: German
Publisher: Peter Lang International Academic Publishing Group
Subject: Languages and Literatures
Added to DOAB on : 2019-01-15 13:31:33
License:

Loading...
Export citation

Choose an application

Abstract

The Russian-German dictionary by Pawlowsky, which first appeared in Riga in 1859, is a little-noticed in Slavic jewel so far. This is astonishing precisely because it is an indispensable tool in reading the Russian classics, its bilingualism is authentic and quite reliable down to scientific nomenclature and also not only records but also explains a great deal of idiomatic and probiotic. The aim of this work is to contribute to the history of Russian-German lexicography through a metalexographic single analysis of this work. The centuries-old disinterest in the results of lexicographical work also explains that Ivan Pawlowsky's Russian-German dictionary, to this day, must be considered terra incognita. Secondary: Pavlovsky's Russian-German dictionary.&#xD;

WeXel oder Die Musik einer Landschaft

Authors: ---
ISBN: 9783205795841 Year: Pages: 646 DOI: 10.26530/oapen_508190 Language: German
Publisher: Böhlau Grant: Austrian Science Fund - PUB 161
Subject: Music
Added to DOAB on : 2014-12-04 09:02:24
License:

Loading...
Export citation

Choose an application

Abstract

Traditional music of the Wechsel, styrian-lower austrian border region, 100 kms south of Vienna. Volume 1 „The religious song“ sung during the farmer’s traditional two-night corpse-watch at the bier in the house of the deceased. 192 songs with text, music and incipits, 3 CDs with historical recordings, dictionary of local dialect.&#xD;CD 1: http://e-book.fwf.ac.at/o:672&#xD;CD 2: http://e-book.fwf.ac.at/o:727&#xD;CD 3: http://e-book.fwf.ac.at/o:762

Selected Papers from the 2018 41st International Conference on Telecommunications and Signal Processing (TSP)

Authors: --- ---
ISBN: 9783039210404 / 9783039210411 Year: Pages: 194 DOI: 10.3390/books978-3-03921-041-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-08-28 11:21:27
License:

Loading...
Export citation

Choose an application

Abstract

This Special Issue contains a series of excellent research works on telecommunications and signal processing, selected from the 2018 41st International Conference on Telecommunications and Signal Processing (TSP) which was held on July 4–6, 2018, in Athens, Greece. The conference was organized in cooperation with the IEEE Region 8 (Europe, Middle East, and Africa), IEEE Greece Section, IEEE Czechoslovakia Section, and IEEE Czechoslovakia Section SP/CAS/COM Joint Chapter by seventeen universities from the Czech Republic, Hungary, Turkey, Taiwan, Japan, Slovak Republic, Spain, Bulgaria, France, Slovenia, Croatia, and Poland, for academics, researchers, and developers, and serves as a premier international forum for the annual exchange and promotion of the latest advances in telecommunication technology and signal processing. The aim of the conference is to bring together both novice and experienced scientists, developers, and specialists, to meet new colleagues, collect new ideas, and establish new cooperation between research groups from universities, research centers, and private sectors worldwide. This collection of 10 papers is highly recommended for researchers, and believed to be interesting, inspiring, and motivating for readers in their further research.

Ultrasound B-mode Imaging: Beamforming and Image Formation Techniques

Authors: --- ---
ISBN: 9783039211999 / 9783039212002 Year: Pages: 146 DOI: 10.3390/books978-3-03921-200-2 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 11:49:15
License:

Loading...
Export citation

Choose an application

Abstract

Ultrasound medical imaging stands out among the other diagnostic imaging modalities for its patient-friendliness, high temporal resolution, low cost, and absence of ionizing radiation. On the other hand, it may still suffer from limited detail level, low signal-to-noise ratio, and narrow field-of-view. In the last decade, new beamforming and image reconstruction techniques have emerged which aim at improving resolution, contrast, and clutter suppression, especially in difficult-to-image patients. Nevertheless, achieving a higher image quality is of the utmost importance in diagnostic ultrasound medical imaging, and further developments are still indispensable. From this point of view, a crucial role can be played by novel beamforming techniques as well as by non-conventional image formation techniques (e.g., advanced transmission strategies, and compounding, coded, and harmonic imaging). This Special Issue includes novel contributions on both ultrasound beamforming and image formation techniques, particularly addressed at improving B-mode image quality and related diagnostic content. This indeed represents a hot topic in the ultrasound imaging community, and further active research in this field is expected, where many challenges still persist.

Learning to Understand Remote Sensing Images

Author:
ISBN: 9783038976844 / 9783038976851 Year: Volume: 1 Pages: 426 DOI: 10.3390/books978-3-03897-685-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2019-12-09 11:49:15
License:

Loading...
Export citation

Choose an application

Abstract

With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.

Keywords

hyperspectral image classification --- SELF --- SVMs --- Segment-Tree Filtering --- multi-sensor --- change feature analysis --- object-based --- multispectral images --- heterogeneous domain adaptation --- transfer learning --- multi-view canonical correlation analysis ensemble --- semi-supervised learning --- canonical correlation weighted voting --- ensemble learning --- image classification --- spatial attraction model (SAM) --- subpixel mapping (SPM) --- land cover --- mixed pixel --- spatial distribution --- hard classification --- building damage detection --- Fuzzy-GA decision making system --- machine learning techniques --- optical remotely sensed images --- sensitivity analysis --- texture analysis --- quality assessment --- ratio images --- Synthetic Aperture Radar (SAR) --- speckle --- speckle filters --- ice concentration --- SAR imagery --- convolutional neural network --- urban surface water extraction --- threshold stability --- sub-pixel --- linear spectral unmixing --- Landsat imagery --- image registration --- image fusion --- UAV --- metadata --- visible light and infrared integrated camera --- semantic segmentation --- CNN --- deep learning --- ISPRS --- remote sensing --- gate --- hyperspectral image --- sparse and low-rank graph --- tensor --- dimensionality reduction --- semantic labeling --- convolution neural network --- fully convolutional network --- sea-land segmentation --- ship detection --- hyperspectral image --- target detection --- multi-task learning --- sparse representation --- locality information --- remote sensing image correction --- color matching --- optimal transport --- CNN --- very high resolution images --- segmentation --- multi-scale clustering --- vehicle localization --- vehicle classification --- high resolution --- aerial image --- convolutional neural network (CNN) --- class imbalance --- deep learning --- convolutional neural network (CNN) --- fully convolutional network (FCN) --- classification --- remote sensing --- high resolution --- semantic segmentation --- deep convolutional neural networks --- manifold ranking --- single stream optimization --- high resolution image --- feature extraction --- hypergraph learning --- morphological profiles --- hyperedge weight estimation --- semantic labeling --- convolutional neural networks --- remote sensing --- deep learning --- aerial images --- hyperspectral image --- feature extraction --- dimensionality reduction --- optimized kernel minimum noise fraction (OKMNF) --- hyperspectral remote sensing --- endmember extraction --- multi-objective --- particle swarm optimization --- image alignment --- feature matching --- geostationary satellite remote sensing image --- GSHHG database --- Hough transform --- dictionary learning --- road detection --- Radon transform --- geo-referencing --- multi-sensor image matching --- Siamese neural network --- satellite images --- synthetic aperture radar --- inundation mapping --- flood --- optical sensors --- spatiotemporal context learning --- Modest AdaBoost --- HJ-1A/B CCD --- GF-4 PMS --- hyperspectral image classification --- automatic cluster number determination --- adaptive convolutional kernels --- hyperspectral imagery --- 1-dimensional (1-D) --- Convolutional Neural Network (CNN) --- Support Vector Machine (SVM) --- Random Forests (RF) --- machine learning --- deep learning --- TensorFlow --- multi-seasonal --- regional land cover --- saliency analysis --- remote sensing --- ROI detection --- hyperparameter sparse representation --- dictionary learning --- energy distribution optimizing --- multispectral imagery --- nonlinear classification --- kernel method --- dimensionality expansion --- deep convolutional neural networks --- road segmentation --- conditional random fields --- satellite images --- aerial images --- THEOS --- land cover change --- downscaling --- sub-pixel change detection --- machine learning --- MODIS --- Landsat --- very high resolution (VHR) satellite image --- topic modelling --- object-based image analysis --- image segmentation --- unsupervised classification --- multiscale representation --- GeoEye-1 --- wavelet transform --- fuzzy neural network --- remote sensing --- conservation --- urban heat island --- land surface temperature --- climate change --- land use --- land cover --- Landsat --- remote sensing --- SAR image --- despeckling --- dilated convolution --- skip connection --- residual learning --- scene classification --- saliency detection --- deep salient feature --- anti-noise transfer network --- DSFATN --- infrared image --- image registration --- MSER --- phase congruency --- hashing --- remote sensing image retrieval --- online learning --- hyperspectral image --- compressive sensing --- structured sparsity --- tensor sparse decomposition --- tensor low-rank approximation

Learning to Understand Remote Sensing Images

Author:
ISBN: 9783038976981 / 9783038976998 Year: Volume: 2 Pages: 376 DOI: 10.3390/books978-3-03897-699-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2019-12-09 11:49:15
License:

Loading...
Export citation

Choose an application

Abstract

With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.

Keywords

hyperspectral image classification --- SELF --- SVMs --- Segment-Tree Filtering --- multi-sensor --- change feature analysis --- object-based --- multispectral images --- heterogeneous domain adaptation --- transfer learning --- multi-view canonical correlation analysis ensemble --- semi-supervised learning --- canonical correlation weighted voting --- ensemble learning --- image classification --- spatial attraction model (SAM) --- subpixel mapping (SPM) --- land cover --- mixed pixel --- spatial distribution --- hard classification --- building damage detection --- Fuzzy-GA decision making system --- machine learning techniques --- optical remotely sensed images --- sensitivity analysis --- texture analysis --- quality assessment --- ratio images --- Synthetic Aperture Radar (SAR) --- speckle --- speckle filters --- ice concentration --- SAR imagery --- convolutional neural network --- urban surface water extraction --- threshold stability --- sub-pixel --- linear spectral unmixing --- Landsat imagery --- image registration --- image fusion --- UAV --- metadata --- visible light and infrared integrated camera --- semantic segmentation --- CNN --- deep learning --- ISPRS --- remote sensing --- gate --- hyperspectral image --- sparse and low-rank graph --- tensor --- dimensionality reduction --- semantic labeling --- convolution neural network --- fully convolutional network --- sea-land segmentation --- ship detection --- hyperspectral image --- target detection --- multi-task learning --- sparse representation --- locality information --- remote sensing image correction --- color matching --- optimal transport --- CNN --- very high resolution images --- segmentation --- multi-scale clustering --- vehicle localization --- vehicle classification --- high resolution --- aerial image --- convolutional neural network (CNN) --- class imbalance --- deep learning --- convolutional neural network (CNN) --- fully convolutional network (FCN) --- classification --- remote sensing --- high resolution --- semantic segmentation --- deep convolutional neural networks --- manifold ranking --- single stream optimization --- high resolution image --- feature extraction --- hypergraph learning --- morphological profiles --- hyperedge weight estimation --- semantic labeling --- convolutional neural networks --- remote sensing --- deep learning --- aerial images --- hyperspectral image --- feature extraction --- dimensionality reduction --- optimized kernel minimum noise fraction (OKMNF) --- hyperspectral remote sensing --- endmember extraction --- multi-objective --- particle swarm optimization --- image alignment --- feature matching --- geostationary satellite remote sensing image --- GSHHG database --- Hough transform --- dictionary learning --- road detection --- Radon transform --- geo-referencing --- multi-sensor image matching --- Siamese neural network --- satellite images --- synthetic aperture radar --- inundation mapping --- flood --- optical sensors --- spatiotemporal context learning --- Modest AdaBoost --- HJ-1A/B CCD --- GF-4 PMS --- hyperspectral image classification --- automatic cluster number determination --- adaptive convolutional kernels --- hyperspectral imagery --- 1-dimensional (1-D) --- Convolutional Neural Network (CNN) --- Support Vector Machine (SVM) --- Random Forests (RF) --- machine learning --- deep learning --- TensorFlow --- multi-seasonal --- regional land cover --- saliency analysis --- remote sensing --- ROI detection --- hyperparameter sparse representation --- dictionary learning --- energy distribution optimizing --- multispectral imagery --- nonlinear classification --- kernel method --- dimensionality expansion --- deep convolutional neural networks --- road segmentation --- conditional random fields --- satellite images --- aerial images --- THEOS --- land cover change --- downscaling --- sub-pixel change detection --- machine learning --- MODIS --- Landsat --- very high resolution (VHR) satellite image --- topic modelling --- object-based image analysis --- image segmentation --- unsupervised classification --- multiscale representation --- GeoEye-1 --- wavelet transform --- fuzzy neural network --- remote sensing --- conservation --- urban heat island --- land surface temperature --- climate change --- land use --- land cover --- Landsat --- remote sensing --- SAR image --- despeckling --- dilated convolution --- skip connection --- residual learning --- scene classification --- saliency detection --- deep salient feature --- anti-noise transfer network --- DSFATN --- infrared image --- image registration --- MSER --- phase congruency --- hashing --- remote sensing image retrieval --- online learning --- hyperspectral image --- compressive sensing --- structured sparsity --- tensor sparse decomposition --- tensor low-rank approximation

Listing 11 - 20 of 20 << page
of 2
>>
Sort by