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

Focal Loss of multi-classification in tensorflow

Multi-Label Image Classification of Chest X-Rays In Pytorch

RetinaNet implementation in PyTorch

An unofficial implementation of ICCV 2017 RetinaNet (Focal Loss).

The implementation of Focal-Loss Using Caffe

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

Focal loss implemention by PyTorch

Focal loss is used instead of Cross Entropy Loss for classification

Implement RetinaNet with TensorFlow.eager

focal loss caffe version

“This repository contains code and results for COVID-19 .”

An intuitive pytorch implementation of softmax focal loss which can be used to train classification and segmentation tasks.

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.

PyTorch implementation of RetinaNet

PyTorch implementation of binary and multi-class focal loss functions

深度学习的损失函数

PyTorch implementation of binary and multi-class focal loss functions

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.

Личный проект в области Computer Vision