Open-ended visual recognition
Visual recognition has traditionally been constrained by closed-set classifications, limiting adaptability to new categories and complex real-world scenarios. This thesis tackles these limitations by leveraging natural language to enhance spatially-aware, open-ended recognition. We first formulate a...
- Autores:
-
González Osorio, Cristina Isabel
- Tipo de recurso:
- Doctoral thesis
- Fecha de publicación:
- 2024
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/75696
- Acceso en línea:
- https://hdl.handle.net/1992/75696
- Palabra clave:
- Artificial Intelligence
Computer Vision
Visual Recognition
Ingeniería
- Rights
- openAccess
- License
- Attribution-NonCommercial-NoDerivatives 4.0 International