1 resultado para Entity-oriented Retrieval
em Bulgarian Digital Mathematics Library at IMI-BAS
Filtro por publicador
- Academic Research Repository at Institute of Developing Economies (3)
- Acceda, el repositorio institucional de la Universidad de Las Palmas de Gran Canaria. España (2)
- AMS Campus - Alm@DL - Università di Bologna (2)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (13)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (24)
- Applied Math and Science Education Repository - Washington - USA (1)
- ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha (5)
- Archive of European Integration (6)
- Aston University Research Archive (1)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (9)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (19)
- Biblioteca Virtual del Sistema Sanitario Público de Andalucía (BV-SSPA), Junta de Andalucía. Consejería de Salud y Bienestar Social, Spain (2)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (118)
- Brock University, Canada (8)
- Bucknell University Digital Commons - Pensilvania - USA (1)
- Bulgarian Digital Mathematics Library at IMI-BAS (1)
- CentAUR: Central Archive University of Reading - UK (95)
- Cochin University of Science & Technology (CUSAT), India (17)
- Comissão Econômica para a América Latina e o Caribe (CEPAL) (8)
- Consorci de Serveis Universitaris de Catalunya (CSUC), Spain (31)
- Cor-Ciencia - Acuerdo de Bibliotecas Universitarias de Córdoba (ABUC), Argentina (2)
- CUNY Academic Works (3)
- Dalarna University College Electronic Archive (2)
- Department of Computer Science E-Repository - King's College London, Strand, London (21)
- Digital Commons @ DU | University of Denver Research (3)
- Digital Commons at Florida International University (1)
- Digital Peer Publishing (3)
- DigitalCommons - The University of Maine Research (1)
- DigitalCommons@The Texas Medical Center (3)
- Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland (37)
- Glasgow Theses Service (1)
- Instituto Politécnico do Porto, Portugal (13)
- Iowa Publications Online (IPO) - State Library, State of Iowa (Iowa), United States (12)
- Martin Luther Universitat Halle Wittenberg, Germany (16)
- Massachusetts Institute of Technology (6)
- Ministerio de Cultura, Spain (2)
- National Center for Biotechnology Information - NCBI (16)
- Publishing Network for Geoscientific & Environmental Data (10)
- Repositório Científico do Instituto Politécnico de Lisboa - Portugal (5)
- Repositório digital da Fundação Getúlio Vargas - FGV (2)
- Repositório Digital da UNIVERSIDADE DA MADEIRA - Portugal (2)
- Repositório do Centro Hospitalar de Lisboa Central, EPE - Centro Hospitalar de Lisboa Central, EPE, Portugal (3)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (38)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (21)
- Scielo Saúde Pública - SP (12)
- Universidad de Alicante (13)
- Universidad del Rosario, Colombia (3)
- Universidad Politécnica de Madrid (57)
- Universidade Complutense de Madrid (1)
- Universidade do Minho (11)
- Universidade Federal do Rio Grande do Norte (UFRN) (3)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (5)
- Université de Lausanne, Switzerland (54)
- Université de Montréal (1)
- Université de Montréal, Canada (9)
- University of Connecticut - USA (2)
- University of Michigan (48)
- University of Queensland eSpace - Australia (18)
- University of Southampton, United Kingdom (4)
- University of Washington (2)
Resumo:
As the volume of image data and the need of using it in various applications is growing significantly in the last days it brings a necessity of retrieval efficiency and effectiveness. Unfortunately, existing indexing methods are not applicable to a wide range of problem-oriented fields due to their operating time limitations and strong dependency on the traditional descriptors extracted from the image. To meet higher requirements, a novel distance-based indexing method for region-based image retrieval has been proposed and investigated. The method creates premises for considering embedded partitions of images to carry out the search with different refinement or roughening level and so to seek the image meaningful content.