YOLO Convolutional neural network for building damage detection in hydrometeorological disasters using satellite imagery

Natural disasters pose a continuous threat to populations worldwide, with hydrometeorological disasters standing out due to their unpredictability, rapid onset, and significant destructive capacity. Consequently, countries invest substantial resources in implementing pre- and post-disaster measures,...

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Autores:
Moreno González, César Luis
Tipo de recurso:
Trabajo de grado de pregrado
Fecha de publicación:
2024
Institución:
Universidad de los Andes
Repositorio:
Séneca: repositorio Uniandes
Idioma:
eng
OAI Identifier:
oai:repositorio.uniandes.edu.co:1992/74680
Acceso en línea:
https://hdl.handle.net/1992/74680
Palabra clave:
Machine Learning
Deep Learning
Computer Vision
Detection Models
Natural Disasters
Hydrometeorological Disasters
Ingeniería
Rights
embargoedAccess
License
https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdf