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Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch
The implementation of focal loss proposed on "Focal Loss for Dense Object Detection" by KM He and support for multi-label dataset.
Caffe implementation of FAIR paper "Focal Loss for Dense Object Detection" for SSD.
Large-Margin Softmax Loss, Angular Softmax Loss, Additive Margin Softmax, ArcFaceLoss And FocalLoss In Tensorflow
RetinaNet implementation in PyTorch
Multi-Label Image Classification of Chest X-Rays In Pytorch
An unofficial implementation of ICCV 2017 RetinaNet (Focal Loss).
the loss function in Aritcal ‘Focal Loss for Dense Object Detection‘’
Label Smoothing applied in Focal Loss
focal loss (multi-class) for lightgbm/xgboost
Pytorch implementation of Class Balanced Loss based on Effective number of Samples
Implement RetinaNet with TensorFlow.eager
Focal loss is used instead of Cross Entropy Loss for classification
“This repository contains code and results for COVID-19 .”
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.
An intuitive pytorch implementation of softmax focal loss which can be used to train classification and segmentation tasks.
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 RetinaNet