Investigating the Potential of Network Optimization for a Constrained Object Detection Problem

Object detection models are usually trained and evaluated on highly complicated, challenging academic datasets, which results in deep networks requiring lots of computations. However, a lot of operational use-cases consist of more constrained situations: they have a limited number of classes to be d...

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Detalles Bibliográficos
Autores principales: Ophoff, Tanguy, Gullentops, Cédric, Van Beeck, Kristof, Goedemé, Toon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321328/
https://www.ncbi.nlm.nih.gov/pubmed/34460514
http://dx.doi.org/10.3390/jimaging7040064

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321328/
https://www.ncbi.nlm.nih.gov/pubmed/34460514
http://dx.doi.org/10.3390/jimaging7040064

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