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Foreground Detection with Deeply Learned Multi-Scale Spatial-Temporal Features
Foreground detection, which extracts moving objects from videos, is an important and fundamental problem of video analysis. Classic methods often build background models based on some hand-craft features. Recent deep neural network (DNN) based methods can learn more effective image features by train...
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| Pubblicato in: | Sensors (Basel) |
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| Autori principali: | , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
MDPI
2018
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6308466/ https://ncbi.nlm.nih.gov/pubmed/30518131 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s18124269 |
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