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IoU Regression with H+L-Sampling for Accurate Detection Confidence
It is a common paradigm in object detection frameworks that the samples in training and testing have consistent distributions for the two main tasks: Classification and bounding box regression. This paradigm is popular in sampling strategy for training an object detector due to its intuition and pra...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8271873/ https://www.ncbi.nlm.nih.gov/pubmed/34203469 http://dx.doi.org/10.3390/s21134433 |