Denoiser_Encoder-With-DNcnn
this project is created based on state of the art model Dncnn . This is a simple implementation of image denoising (by AmzadHossainrafis)
classification
Classification of the MNIST dataset using various Deep Learning techniques (by giakou4)
| Denoiser_Encoder-With-DNcnn | classification | |
|---|---|---|
| 1 | 1 | |
| 1 | 20 | |
| - | - | |
| 10.0 | 0.0 | |
| almost 2 years ago | over 1 year ago | |
| Python | Python | |
| - | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Denoiser_Encoder-With-DNcnn
Posts with mentions or reviews of Denoiser_Encoder-With-DNcnn.
We have used some of these posts to build our list of alternatives
and similar projects.
-
DNcnn: Residual Learning of Deep CNN for Image Denoising.
project git: https://github.com/AmzadHossainrafis/Denoiser_Encoder-With-DNcnn
classification
Posts with mentions or reviews of classification.
We have used some of these posts to build our list of alternatives
and similar projects.
-
PyTorch Ensemble model
I created a CNN for a classification problem using 2 different techniques: 1) conventional CNN and 2) contrastive learning (SimCLR framework). As a reference code, I attack the starting point of my coding: https://github.com/giakou4/MNIST_classification.
What are some alternatives?
When comparing Denoiser_Encoder-With-DNcnn and classification you can also consider the following projects:
disentangling-vae - Experiments for understanding disentanglement in VAE latent representations
convolution-vision-transformers - PyTorch Implementation of CvT: Introducing Convolutions to Vision Transformers
dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).
pytorch-sentiment-analysis - Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
Image-Forgery-Detection-CNN - Image forgery detection using convolutional neural networks. Group 10's final project for TU Delft's course CS4180 Deep Learning 2019.