jaccardSegment
Jaccard loss framework
A deep learning framework implementing Deeplab-resnet-101 with binary Jaccard loss surrogate, based on the Lovász hinge loss.
Deeplab-resnet-101 in Pytorch with Jaccard loss
97 stars
8 watching
21 forks
Language: Python
last commit: over 7 years ago
Linked from 1 awesome list
mrgloom/awesome-semantic-segmentationRelated projects:
| Repository | Description | Stars |
|---|---|---|
 hanxunh/active-passive-losses | A PyTorch-based framework for implementing normalized loss functions to improve deep learning model robustness against noisy labels. | 134 |
 giorgiop/loss-correction | Provides a framework for implementing robust loss functions to mitigate the effects of label noise in deep neural networks. | 88 |
 coincheung/pytorch-loss | Provides a comprehensive set of implementation of various loss functions and operators for deep learning models | 2,181 |
 hannes-brt/hebel | A Python library for GPU-accelerated deep learning | 1,169 |
 mblondel/fenchel-young-losses | Provides Fenchel-Young losses for probabilistic classification in PyTorch/TensorFlow/scikit-learn. | 183 |
 alanchou/truncated-loss | An implementation of a loss function designed to improve the training of deep neural networks with noisy labels | 125 |
 mop/bier | This project implements a deep metric learning framework using an adversarial auxiliary loss to improve robustness. | 39 |
 isht7/pytorch-deeplab-resnet | A deep learning model implementation of the DeepLab ResNet architecture for image segmentation tasks. | 602 |
 hjmshi/pytorch-lbfgs | A PyTorch implementation of L-BFGS optimization algorithm for training neural networks | 586 |
 princetonvision/marvin | A minimalistic GPU-only framework for building N-dimensional ConvNet neural networks | 421 |
 jbarrow/lambdanet | An artificial neural network library for rapid prototyping and extension in Haskell. | 377 |
 jankrepl/deepdow | A framework that enables portfolio optimization using deep learning. | 920 |
 ahmedfgad/geneticalgorithmpython | A Python library for building and optimizing machine learning algorithms using a genetic algorithm | 1,887 |
 rlouf/mcx | Tools and methods for Bayesian deep learning using probabilistic programming. | 325 |
 google-deepmind/jraph | A lightweight library for working with graph neural networks in jax. | 1,375 |