Connectionist Temporal Classification (CTC) decoding algorithms: best path, beam search, lexicon search, prefix search, and token passing. Implemented in Python.

Official Pytorch Implementation of: "Asymmetric Loss For Multi-Label Classification"(ICCV, 2021) paper

[ICCV 2021] Focal Frequency Loss for Image Reconstruction and Synthesis

face recognition training project(pytorch)

遥感图像的语义分割，基于深度学习，在Tensorflow框架下，利用TF.Keras，运行环境TF2.0+

Ever wondered how to code your Neural Network using NumPy, with no frameworks involved?

Reproducing experimental results of LL4AL [Yoo et al. 2019 CVPR]

Prostate MR Image Segmentation 2012

YOLOv4 Pytorch implementation with all freebies and specials and 15+ more exclusive improvements. Easy to use!

Loss modelling framework.

Torchélie is a set of utility functions, layers, losses, models, trainers and other things for PyTorch.

Code for the paper "Facial Emotion Recognition: State of the Art Performance on FER2013"

Focal Loss of multi-classification in tensorflow

An implementation for mnist center loss training and visualization

Library for testing and measuring network loss and latency between distributed endpoints.

Deep Attentive Center Loss

Prostate MR Image Segmentation 2012

a simple pytorch implement of Multi-Sample Dropout

Weighted Focal Loss for multilabel classification

Implementation of "Anchor Loss: Modulating loss scale based on prediction difficulty"