• português (Brasil)
    • English
    • español
  • English 
    • português (Brasil)
    • English
    • español
  • Login
About
  • Policies
  • Instructions to authors
  • Contact
    • Policies
    • Instructions to authors
    • Contact
View Item 
  •   Home
  • Centro de Ciências Exatas e de Tecnologia - CCET
  • Programas de Pós-Graduação
  • Ciência da Computação - PPGCC
  • Teses e dissertações
  • View Item
  •   Home
  • Centro de Ciências Exatas e de Tecnologia - CCET
  • Programas de Pós-Graduação
  • Ciência da Computação - PPGCC
  • Teses e dissertações
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsAdvisorTitlesSubjectsCNPq SubjectsGraduate ProgramDocument TypeThis CollectionBy Issue DateAuthorsAdvisorTitlesSubjectsCNPq SubjectsGraduate ProgramDocument Type

My Account

Login

Estratégias para delimitação de regiões de interesse na visualização de consultas por similaridades

Thumbnail
View/Open
Dissertação Claudio Eduardo Paiva (1.583Mb)
Date
2018-11-01
Author
Paiva, Claudio Eduardo
Metadata
Show full item record
Abstract
The increase in data volume that has been occurring in recent time has generated the need for new methods of storing and retrieving information not only for the well known conventional data but also for the complex data such as images. In an image database, content-based searches can be done by comparing image characteristics such as color, texture, and shape to find objects similar to a particular search image. The fact, which people can do visual analysis more efficiently than in other ways, makes data visualization an important ally in creating knowledge in many different areas. Therefore, this study aims at analysing ways of visualizing the results of queries similarity in complex data, limiting itself only to the region that the query is being carried out, mapping the data in three-dimensional space and allowing users to interact with them, by changing the visualisation and being favored by the human perception to improve the analysis and the understanding of the data.
URI
https://repositorio.ufscar.br/handle/ufscar/10876
Collections
  • Teses e dissertações

UFSCar
Universidade Federal de São Carlos - UFSCar
Send Feedback

UFSCar

IBICT
 

 


UFSCar
Universidade Federal de São Carlos - UFSCar
Send Feedback

UFSCar

IBICT