16 resultados para Agui, 1717-1797
Filtro por publicador
- Acceda, el repositorio institucional de la Universidad de Las Palmas de Gran Canaria. España (10)
- Andina Digital - Repositorio UASB-Digital - Universidade Andina Simón Bolívar (2)
- Aquatic Commons (3)
- Archive of European Integration (2)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (2)
- Biblioteca de Teses e Dissertações da USP (1)
- Biblioteca Digital da Câmara dos Deputados (4)
- Biblioteca Digital de la Universidad Católica Argentina (2)
- Biblioteca Digital de Teses e Dissertações Eletrônicas da UERJ (1)
- Biblioteca Valenciana Digital - Ministerio de Educación, Cultura y Deporte - Valencia - Espanha (20)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (9)
- Boston University Digital Common (2)
- Brock University, Canada (20)
- CaltechTHESIS (1)
- Cámara de Comercio de Bogotá, Colombia (2)
- Cambridge University Engineering Department Publications Database (9)
- CentAUR: Central Archive University of Reading - UK (2)
- Center for Jewish History Digital Collections (11)
- Chinese Academy of Sciences Institutional Repositories Grid Portal (46)
- Cochin University of Science & Technology (CUSAT), India (1)
- CORA - Cork Open Research Archive - University College Cork - Ireland (3)
- Digitale Sammlungen - Goethe-Universität Frankfurt am Main (11)
- Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland (1)
- DRUM (Digital Repository at the University of Maryland) (1)
- Duke University (1)
- eResearch Archive - Queensland Department of Agriculture; Fisheries and Forestry (2)
- Gallica, Bibliotheque Numerique - Bibliothèque nationale de France (French National Library) (BnF), France (307)
- Greenwich Academic Literature Archive - UK (3)
- Harvard University (188)
- Helda - Digital Repository of University of Helsinki (14)
- Indian Institute of Science - Bangalore - Índia (12)
- Infoteca EMBRAPA (3)
- Instituto de Engenharia Nuclear, Brazil - Carpe dIEN (2)
- Instituto Politécnico do Porto, Portugal (1)
- Memoria Académica - FaHCE, UNLP - Argentina (5)
- Ministerio de Cultura, Spain (12)
- Plymouth Marine Science Electronic Archive (PlyMSEA) (2)
- Portal de Revistas Científicas Complutenses - Espanha (2)
- Publishing Network for Geoscientific & Environmental Data (46)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (16)
- Queensland University of Technology - ePrints Archive (15)
- RDBU - Repositório Digital da Biblioteca da Unisinos (1)
- Repositorio Académico de la Universidad Nacional de Costa Rica (1)
- Repositorio Academico Digital UANL (1)
- Repositório Alice (Acesso Livre à Informação Científica da Embrapa / Repository Open Access to Scientific Information from Embrapa) (3)
- REPOSITORIO DIGITAL IMARPE - INSTITUTO DEL MAR DEL PERÚ, Peru (2)
- Repositorio Institucional de la Universidad Nacional Agraria (2)
- Repositorio Institucional de la Universidad Pública de Navarra - Espanha (2)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (11)
- SAPIENTIA - Universidade do Algarve - Portugal (4)
- South Carolina State Documents Depository (6)
- Universidad Autónoma de Nuevo León, Mexico (15)
- Universidad de Alicante (1)
- Universidad del Rosario, Colombia (14)
- Universidade de Lisboa - Repositório Aberto (2)
- Universidade Federal do Rio Grande do Norte (UFRN) (1)
- Universitat de Girona, Spain (2)
- Université de Lausanne, Switzerland (1)
- Université de Montréal, Canada (5)
- University of Michigan (121)
- University of Queensland eSpace - Australia (1)
- University of Southampton, United Kingdom (1)
Resumo:
We propose a spatio-temporal rich model of motion vector planes as a part of a full steganalytic system against motion vector based steganography. Superior detection accuracy of the rich model over the previous methods has been lately demonstrated for digital images in both spatial and DCT domain. It has not been heretofore used for detection of motion vector steganography. We also introduced a transformation so as to extend the feature set with temporal residuals. We carried out the tests along with most recent motion vector steganalysis and steganography methods. Test results show that the proposed model delivers an outstanding performance compared to the previous methods.