Vehicle Detection in Aerial Images Based on Region Convolutional Neural Networks and Hard Negative Example Mining

Detecting vehicles in aerial imagery plays an important role in a wide range of applications. The current vehicle detection methods are mostly based on sliding-window search and handcrafted or shallow-learning-based features, having limited description capability and heavy computational costs. Recen...

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Detalles Bibliográficos
Autores principales: Tang, Tianyu, Zhou, Shilin, Deng, Zhipeng, Zou, Huanxin, Lei, Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5335960/
https://www.ncbi.nlm.nih.gov/pubmed/28208587
http://dx.doi.org/10.3390/s17020336

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5335960/
https://www.ncbi.nlm.nih.gov/pubmed/28208587
http://dx.doi.org/10.3390/s17020336

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