Check order status

Become part of a community of book lovers from all over the world and get access to a whole bunch of benefits. Create an account for free

DPD courier 4.99 € GLS courier 9.99 €

Contact

How to shop

Help

My account

▸ Empty :-(

Knowledge Transfer between Computer Vision and Text Mining

Similarity-based Learning Approaches

Radu Tudor Ionescu

Marius Popescu

Language

English

Book Paperback

Libristo code: 20118522

Publishers Springer International Publishing AG, May 2018

This ground-breaking text/reference diverges from the traditional view that computer vision (for ima... Full description

Libristo code: 20118522

249 b

102.38 €

In stock at our supplier Shipping in 8-11 days

Up to 30 days for returns

Customers also purchased

LEGO NINJAGO. Uwolnić Smoka Chaosu! Opracowanie zbiorowe

Paperback

5.02 €

Ricette migranti. 20 piatti, 20 storie di vita Elena Guerra

Paperback

23.13 €

Rare Selena Gomez Audio

Audio vinyl

31.27 €

Perversionen der Frau Estela V. Welldon

Paperback

31.77 €

Pióro wieczne My.Pen dla praworęcznych różowo-białe

binding.

10.55 €

Mehrsprachigkeit aus neurolinguistischer Sicht Gerda Videsott

Hardback

63.75 €

Fuhrung im Original Alfred Essenwanger

Adobe ePub DRM

26.25 €

Stalin und der Stalinismus Jörg Baberowski

Paperback

12.56 €

Wie Laborratten Anna Gasthauser

Paperback

12.56 €

Analisis Economico del Processo Civil T. Gico Ivo Jr.

Hardback

42.94 €

Guia de lectura Las penas del joven Werther de Goethe (analisis literario de referencia y resumen completo) Goethe

Paperback

7.63 €

Maria Antonietta. Il diario segreto di una regina Benjamin Lacombe

Hardback

28.65 €

Linee blocco appunti Britta Kante

Paperback

7.73 €

Be in Joy Dhira Nitai

Paperback

18.70 €

This ground-breaking text/reference diverges from the traditional view that computer vision (for image analysis) and string processing (for text mining) are separate and unrelated fields of study, propounding that images and text can be treated in a similar manner for the purposes of information retrieval, extraction and classification. Highlighting the benefits of knowledge transfer between the two disciplines, the text presents a range of novel similarity-based learning (SBL) techniques founded on this approach. Topics and features: describes a variety of SBL approaches, including nearest neighbor models, local learning, kernel methods, and clustering algorithms; presents a nearest neighbor model based on a novel dissimilarity for images; discusses a novel kernel for (visual) word histograms, as well as several kernels based on a pyramid representation; introduces an approach based on string kernels for native language identification; contains links for downloading relevant open source code.