Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch
翻译 - 实施EfficientDet：PyTorch中的可扩展且高效的对象检测
Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection, NeurIPS2020
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
#计算机科学#Multi-Label Image Classification of Chest X-Rays In Pytorch
RetinaNet implementation 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
Pytorch implementation of Class Balanced Loss based on Effective number of Samples
focal loss (multi-class) for lightgbm/xgboost
Implement RetinaNet with TensorFlow.eager
Focal loss is used instead of Cross Entropy Loss for classification
#计算机科学#“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.