Deep learning for small object detection
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http://hdl.handle.net/10347/24470
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Título: | Deep learning for small object detection |
Autor/a: | Bosquet Mera, Brais |
Dirección/Titoría: | Mucientes Molina, Manuel Brea Sánchez, Víctor M. |
Centro/Departamento: | Universidade de Santiago de Compostela. Escola de Doutoramento Internacional (EDIUS) Universidade de Santiago de Compostela. Programa de Doutoramento en Investigación en Tecnoloxías da Información |
Palabras chave: | small object detection | convolutional neural networks (CNNs) | generative adversarial networks (GANs) | deep learning | spatio-temporal convolutional network | data augmentation | object linkin | |
Data: | 2020 |
Resumo: | Small object detection has become increasingly relevant due to the fact that the performance of common object detectors falls significantly as objects become smaller. Many computer vision applications require the analysis of the entire set of objects in the image, including extremely small objects. Moreover, the detection of small objects allows to perceive objects at a greater distance, thus giving more time to adapt to any situation or unforeseen event. |
URI: | http://hdl.handle.net/10347/24470 |
Dereitos: | Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
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