Knowledge Transfer between Computer Vision and Text Mining: Similarity-based Learning Approaches: 0 (Advances in Computer Vision and Pattern Recognition) - Tapa dura

Acerca del autor

Dr. Radu Tudor Ionescu is an Assistant Professor in the Department of Computer Science at the University of Bucharest, Romania.
Dr. Marius Popescu is an Associate Professor at the same institution.

De la contraportada

This ground-breaking text/reference diverges from thetraditional view that computer vision (for image analysis) and stringprocessing (for text mining) are separate and unrelated fields of study,propounding that images and text can be treated in a similar manner for thepurposes of information retrieval, extraction and classification. Highlightingthe benefits of knowledge transfer between the two disciplines, the textpresents a range of novel similarity-based learning techniques founded on thisapproach.

Topics and features:

• Describes avariety of similarity-based learning approaches, including nearest neighbormodels, local learning, kernel methods, and clustering algorithms
• Presents anearest neighbor model based on a novel dissimilarity for images, and appliesthis for handwritten digit recognition and texture analysis
• Discusses anovel kernel for (visual) word histograms, as well as several kernels based on pyramid representation, and uses these for facial expression recognition andtext categorization by topic
• Introduces anapproach based on string kernels for native language identification
• Contains linksfor downloading relevant open source code
• With a forewordby Prof. Florentina Hristea

This unique work will be of great benefit toresearchers, postgraduate and advanced undergraduate students involved inmachine learning, data science, text mining and computer vision.

Dr. Radu Tudor Ionescu is an AssistantProfessor in the Department of Computer Science at the University of Bucharest,Romania. Dr. Marius Popescu is an AssociateProfessor at the same institution.