CvT VS assembled-cnn

Compare CvT vs assembled-cnn and see what are their differences.

CvT

This is an official implementation of CvT: Introducing Convolutions to Vision Transformers. (by microsoft)

assembled-cnn

Tensorflow implementation of "Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network" (by clovaai)
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CvT assembled-cnn
2 1
515 330
4.1% 0.6%
0.0 0.0
12 months ago over 3 years ago
Python Python
MIT License Apache License 2.0
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.

CvT

Posts with mentions or reviews of CvT. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-05-16.

assembled-cnn

Posts with mentions or reviews of assembled-cnn. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing CvT and assembled-cnn you can also consider the following projects:

datumaro - Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.

biprop - Identify a binary weight or binary weight and activation subnetwork within a randomly initialized network by only pruning and binarizing the network.

convolution-vision-transformers - PyTorch Implementation of CvT: Introducing Convolutions to Vision Transformers

cvat - Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. [Moved to: https://github.com/cvat-ai/cvat]

create-go-app - ✨ A complete and self-contained solution for developers of any qualification to create a production-ready project with backend (Go), frontend (JavaScript, TypeScript) and deploy automation (Ansible, Docker) by running only one CLI command.

Naruto_Handsign_Classification - Naruto Hand Gesture Recognition with OpenCV and Transfer Learning

autogluon - AutoGluon: AutoML for Image, Text, Time Series, and Tabular Data [Moved to: https://github.com/autogluon/autogluon]

autogluon - Fast and Accurate ML in 3 Lines of Code

One-Piece-Image-Classifier - A quick image classifier trained with manually selected One Piece images.