Free delivery for orders over 69.99€

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

Free delivery for purchases over 69.99 €

Speedy courier 3.49 € Speedy point 3.49 € Еконт courier 3.99 € Еконтомат/Офис на Еконт 3.99 € Ekont Box 3.99 € Sameday courier 3.99 € Sameday Box 3.99 € Box Now 3.99 €

Contact

How to shop

Help

My account

▸ Empty :-(

Free delivery for orders over 69.99€

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

263 b

108.72 €

212.63 лв

In stock at our supplier Shipping in 8-11 days

Up to 30 days for returns

Customers also purchased

Linee blocco appunti Britta Kante

Paperback

7.66 € 14.98 лв

LEGO NINJAGO. Uwolnić Smoka Chaosu! Opracowanie zbiorowe

Paperback

5.43 € 10.63 лв

Fermate Kowalsky! Tangentopoli trent'anni dopo Vittorio Nessi

Paperback

23.98 € 46.89 лв

Fuhrung im Original Alfred Essenwanger

Adobe ePub DRM

27.71 € 54.19 лв

Wie Laborratten Anna Gasthauser

Paperback

13.46 € 26.33 лв

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

Paperback

24.60 € 48.11 лв

Analisis Economico del Processo Civil T. Gico Ivo Jr.

Hardback

42.11 € 82.35 лв

Be in Joy Dhira Nitai

Paperback

19.78 € 38.69 лв

Stalin und der Stalinismus Jörg Baberowski

Paperback

13.46 € 26.33 лв

Mehrsprachigkeit aus neurolinguistischer Sicht Gerda Videsott

Hardback

67.80 € 132.60 лв

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.