dropblock
Convolutional regularizer
Regularizes convolutional networks by randomly dropping units in contiguous regions of feature maps
Implementation of DropBlock: A regularization method for convolutional networks in PyTorch.
588 stars
9 watching
95 forks
Language: Python
last commit: over 4 years ago computer-visionconvolutional-neural-networksdropblockdropoutmachine-learningpytorchpytorch-implementationregularization
Related projects:
Repository | Description | Stars |
---|---|---|
ijindal/noisy_dropout_regularization | This project explores training deep neural networks using noisy labels with dropout regularization to improve robustness. | 11 |
zalandoresearch/pytorch-dilated-rnn | Implementations of Dilated Recurrent Neural Networks in PyTorch | 211 |
pp00704831/banet-tip-2022 | A PyTorch implementation of an attention network for dynamic scene deblurring | 37 |
luuuyi/cbam.pytorch | PyTorch implementation of the CBAM module for refining feature maps in deep networks | 1,337 |
yukkyo/pytorch-filterresponsenormalizationlayer | An implementation of Filter Response Normalization Layer in PyTorch to improve the training of deep neural networks by eliminating batch dependence. | 85 |
szagoruyko/binary-wide-resnet | An implementation of a 1-bit weight neural network architecture using PyTorch | 124 |
hitcszx/lnl_sr | An implementation of a regularization technique to improve the accuracy of deep learning models trained with noisy labels. | 46 |
codeslake/ifan | Implementation of an algorithm for single image deblurring in images with defocus blur | 227 |
deepinsight-pcalab/compactbilinearpooling-pytorch | A PyTorch implementation of compact bilinear pooling, an efficient downsampling technique used in computer vision and other image processing applications. | 182 |
1zb/deformable-convolution-pytorch | An implementation of Deformable Convolution in PyTorch using CUDA. | 409 |
jacobgil/pytorch-pruning | This project provides a PyTorch implementation of pruning techniques to reduce the computational resources required for neural network inference. | 875 |
ahmedfgad/numpycnn | An implementation of a convolutional neural network (CNN) using NumPy for basic classification tasks. | 570 |
tengshaofeng/residualattentionnetwork-pytorch | Implementing a deep learning framework for image classification using Residual Attention Network architecture | 680 |
randl/shufflenetv2-pytorch | An implementation of a lightweight convolutional neural network architecture for mobile devices | 191 |
chosj95/mimo-unet | Develops a deep learning model for single image deblurring with improved performance and computational efficiency | 373 |