A Deep-Learning Model with Task-Specific Bounding Box Regressors and Conditional Back-Propagation for Moving Object Detection in ADAS Applications

This paper proposes a deep-learning model with task-specific bounding box regressors (TSBBRs) and conditional back-propagation mechanisms for detection of objects in motion for advanced driver assistance system (ADAS) applications. The proposed model separates the object detection networks for objec...

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Detalles Bibliográficos
Autores principales: Lin, Guan-Ting, Malligere Shivanna, Vinay, Guo, Jiun-In
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571112/
https://www.ncbi.nlm.nih.gov/pubmed/32942628
http://dx.doi.org/10.3390/s20185269

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571112/
https://www.ncbi.nlm.nih.gov/pubmed/32942628
http://dx.doi.org/10.3390/s20185269

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