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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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| Publié dans: | Sensors (Basel) |
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| Auteurs principaux: | , , , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
MDPI
2017
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5335960/ https://ncbi.nlm.nih.gov/pubmed/28208587 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s17020336 |
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