jhkim89/PyramidNet

Torch implementation of the paper "Deep Pyramidal Residual Networks" (https://arxiv.org/abs/1610.02915).

39
/ 100
Emerging

This project offers a specialized method for improving image recognition systems. It takes raw image data and processes it through a novel network architecture to produce highly accurate classifications. Researchers and engineers working on computer vision tasks will find this useful for developing advanced image classification models.

129 stars. No commits in the last 6 months.

Use this if you are a researcher or engineer looking to achieve state-of-the-art accuracy in image classification tasks, especially on datasets like CIFAR and ImageNet.

Not ideal if you are not experienced with deep learning frameworks like Torch or if your primary goal is not image classification.

image-classification deep-learning-research computer-vision neural-network-architecture
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 21 / 25

How are scores calculated?

Stars

129

Forks

39

Language

Lua

License

—

Category

cifar-10-image-classification

Last pushed

Oct 31, 2017

Commits (30d)

0

GitHub
CIFAR 10 Image Classification · 111 frameworks

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/jhkim89/PyramidNet"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.

Higher-rated alternatives

raghakot/keras-resnet

Residual networks implementation using Keras-1.0 functional API

51

titu1994/DenseNet

DenseNet implementation in Keras

51

liuzhuang13/DenseNet

Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award).

51

BIGBALLON/cifar-10-cnn

Play deep learning with CIFAR datasets

51

bamos/densenet.pytorch

A PyTorch implementation of DenseNet.

51

Explore ML Frameworks

All categories Trending ML Framework directory Insights