1 resultado para Tourist marketing
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)
Filtro por publicador
- Aberystwyth University Repository - Reino Unido (3)
- Andina Digital - Repositorio UASB-Digital - Universidade Andina Simón Bolívar (11)
- Aquatic Commons (58)
- Archive of European Integration (8)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (88)
- B-Digital - Universidade Fernando Pessoa - Portugal (3)
- Biblioteca Digital da Câmara dos Deputados (1)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (1)
- Biblioteca Digital de la Universidad Católica Argentina (1)
- Biblioteca Digital de Teses e Dissertações Eletrônicas da UERJ (2)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (1)
- Brock University, Canada (14)
- Cámara de Comercio de Bogotá, Colombia (12)
- Cambridge University Engineering Department Publications Database (5)
- CentAUR: Central Archive University of Reading - UK (74)
- Cochin University of Science & Technology (CUSAT), India (21)
- Cornell: DigitalCommons@ILR (1)
- Corvinus Research Archive - The institutional repository for the Corvinus University of Budapest (1)
- Dalarna University College Electronic Archive (3)
- Digital Archives@Colby (1)
- Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland (6)
- Duke University (1)
- eResearch Archive - Queensland Department of Agriculture; Fisheries and Forestry (3)
- FAUBA DIGITAL: Repositorio institucional científico y académico de la Facultad de Agronomia de la Universidad de Buenos Aires (7)
- Greenwich Academic Literature Archive - UK (5)
- Helda - Digital Repository of University of Helsinki (17)
- Indian Institute of Science - Bangalore - Índia (3)
- Instituto Politécnico do Porto, Portugal (22)
- Ministerio de Cultura, Spain (36)
- Portal de Revistas Científicas Complutenses - Espanha (1)
- QSpace: Queen's University - Canada (1)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (43)
- Queensland University of Technology - ePrints Archive (176)
- ReCiL - Repositório Científico Lusófona - Grupo Lusófona, Portugal (13)
- Repositório Científico do Instituto Politécnico de Lisboa - Portugal (9)
- Repositório Científico do Instituto Politécnico de Santarém - Portugal (5)
- Repositório Institucional da Universidade de Aveiro - Portugal (3)
- Repositório Institucional da Universidade Federal do Rio Grande do Norte (2)
- Repositorio Institucional de la Universidad Pública de Navarra - Espanha (5)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (1)
- Research Open Access Repository of the University of East London. (1)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (38)
- SAPIENTIA - Universidade do Algarve - Portugal (13)
- Universidad Autónoma de Nuevo León, Mexico (3)
- Universidad de Alicante (1)
- Universidad del Rosario, Colombia (56)
- Universidad Politécnica Salesiana Ecuador (1)
- Universidade de Lisboa - Repositório Aberto (2)
- Universidade dos Açores - Portugal (1)
- Universidade Federal do Rio Grande do Norte (UFRN) (6)
- Universitat de Girona, Spain (3)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (2)
- Université de Lausanne, Switzerland (1)
- Université de Montréal, Canada (7)
- University of Southampton, United Kingdom (5)
- WestminsterResearch - UK (10)
- Worcester Research and Publications - Worcester Research and Publications - UK (1)
Resumo:
In this paper, we present a study on a deterministic partially self-avoiding walk (tourist walk), which provides a novel method for texture feature extraction. The method is able to explore an image on all scales simultaneously. Experiments were conducted using different dynamics concerning the tourist walk. A new strategy, based on histograms. to extract information from its joint probability distribution is presented. The promising results are discussed and compared to the best-known methods for texture description reported in the literature. (C) 2009 Elsevier Ltd. All rights reserved.