PyTorch implementation of RetinaNet
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Updated
Apr 17, 2018 - Python
PyTorch implementation of RetinaNet
Non-profit and operations analyst learning as much as she can about data science theory and application in hopes to one day use her superpowers for good.
PyTorch implementation of focal loss for multi-class semantic segmentation
PyTorch implementation of polyloss and cyclic focal loss and their performance with sample dataset/s.
“This repository contains code and results for COVID-19 .”
Focal loss is used instead of Cross Entropy Loss for classification
Implement RetinaNet with TensorFlow.eager
Pytorch implementation of Class Balanced Loss based on Effective number of Samples
Label Smoothing applied in Focal Loss
the loss function in Aritcal ‘Focal Loss for Dense Object Detection‘’
An unofficial implementation of ICCV 2017 RetinaNet (Focal Loss).
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