Topics / #convolutional-neural-networks

Convolutional-neural-networks projects on GitHub

Image-processing neural networks used for classification, segmentation, and super resolution.

As of October 19, 2026, the most-starred Convolutional-neural-networks projects on GitHub are Deep-Learning-Papers-Reading-Roadmap (39.6K stars), deep-learning-for-image-processing (26.4K stars) and Anime4K (21.5K stars). GitHub.Locker tracks 17 Convolutional-neural-networks repositories with 257.8K stars combined. The fastest-growing on October 18 was Anime4K, with +7 stars in a day.

17Projects

257.8KStars in total

+23Stars in a day

Browse in the catalog →github.com/topics/convolutional-neural-networks ↗

Hot right now

Most stars gained in a day · Oct 18

Anime4K

bloc97/Anime4K · ★ 21.5K

Anime4K is a set of open-source, real-time upscaling and denoising algorithms, implemented as GLSL shaders, that sharpen and upscale anime video on the fly inside your media player instead of permanently re-encoding the file.

Deep-Learning-Papers-Reading-Roadmap

floodsung/Deep-Learning-Papers-Reading-Roadmap · ★ 39.6K

A curated, structured reading roadmap of landmark deep learning papers, organized to guide a newcomer from history and basics through methods and applications to the state of the art.

deep-learning-for-image-processing

WZMIAOMIAO/deep-learning-for-image-processing · ★ 26.4K

A video-based deep learning course that walks through classic computer-vision architectures for image classification, object detection, segmentation and keypoint detection, pairing each network with a lecture and runnable code.

deeplearning_ai_books

fengdu78/deeplearning_ai_books · ★ 21.2K

A Chinese-language collection of notes covering Andrew Ng's (吴恩达) Deep Learning Specialization on Coursera — five courses on neural networks, hyperparameter tuning, structuring ML projects, CNNs, and sequence models.

The all-time top

17 projects · by stars

#1 · floodsung/Deep-Learning-Papers-Reading-Roadmap
Deep-Learning-Papers-Reading-Roadmap
A curated, structured reading roadmap of landmark deep learning papers, organized to guide a newcomer from history and basics through methods and applications to the state of the art.
39.6K
#2 · WZMIAOMIAO/deep-learning-for-image-processing
deep-learning-for-image-processing
A video-based deep learning course that walks through classic computer-vision architectures for image classification, object detection, segmentation and keypoint detection, pairing each network with a lecture and runnable code.
26.4K
#3 · bloc97/Anime4K
Anime4K
Anime4K is a set of open-source, real-time upscaling and denoising algorithms, implemented as GLSL shaders, that sharpen and upscale anime video on the fly inside your media player instead of permanently re-encoding the file.
21.5K

4
deeplearning_ai_books
21.2Kfengdu78/deeplearning_ai_books · HTML
A Chinese-language collection of notes covering Andrew Ng's (吴恩达) Deep Learning Specialization on Coursera — five courses on neural networks, hyperparameter tuning, structuring ML projects, CNNs, and sequence models.
5
deeplearning-models
17.6Krasbt/deeplearning-models · Jupyter Notebook
A large collection of Jupyter Notebooks implementing various deep learning architectures, models, and training tips for TensorFlow and PyTorch.
6
brain.js
14.9KBrainJS/brain.js · TypeScript
brain.js is a GPU-accelerated neural network library written in JavaScript that runs in both browsers and Node.js. It is a continuation of the unmaintained harthur/brain project.
7
conv_arithmetic
14.7Kvdumoulin/conv_arithmetic · TeX
This is a technical report (paper) explaining convolution arithmetic in deep learning, paired with a set of animated GIFs that visualize how different convolution operations behave.
8
fashion-mnist
12.9Kzalandoresearch/fashion-mnist · Python
A dataset of Zalando's article images for benchmarking machine learning algorithms: 60,000 training and 10,000 test examples, each a 28x28 grayscale image with a label from 10 classes. It is meant as a direct drop-in replacement for the original MNIST.
9
External-Attention-pytorch
12.2Kxmu-xiaoma666/External-Attention-pytorch · Python
A PyTorch collection of Attention, Backbone, MLP, Re-parameter, and Convolution implementations from research papers, meant to help you understand papers by seeing their mechanisms coded up.
10
Pytorch-UNet
11.7Kmilesial/Pytorch-UNet · Python
A PyTorch implementation of the U-Net convolutional network for semantic segmentation, customized for Kaggle's Carvana Image Masking Challenge on high-definition images.
11
convnetjs
11.2Kkarpathy/convnetjs · JavaScript
ConvNetJS is a JavaScript implementation of neural networks that lets you train Convolutional Neural Networks, ordinary fully-connected nets, and even reinforcement learning agents directly in the browser.
12
cs231n.github.io
11.1Kcs231n/cs231n.github.io · Jupyter Notebook
This is the public notes and assignments page for Stanford's CS231n course on Convolutional Neural Networks for Visual Recognition.
13
fast-style-transfer
11Klengstrom/fast-style-transfer · Python
This is a TensorFlow implementation of fast neural style transfer: once trained, it applies the artistic style of a painting to a photo or video in a fraction of a second, building on the Gatys, Johnson, and Ulyanov style-transfer papers.
14
pix2pix
10.7Kphillipi/pix2pix · Lua
This is the original Torch/Lua implementation accompanying the pix2pix paper (CVPR 2017), which learns to translate images from one style into another — e.g. label maps to photos, or sketches to shoes — using a conditional GAN.
15
yolov3
10.6Kultralytics/yolov3 · Python
Ultralytics' PyTorch implementation of the YOLOv3 real-time object detector, packaging three model variants - YOLOv3, YOLOv3-SPP and YOLOv3-tiny - with training, validation, inference and multi-format export tooling.
16
techniques
10.3Ksatellite-image-deep-learning/techniques
A curated list of techniques for deep learning with satellite and aerial imagery, covering architectures, models and algorithms for tasks like classification, segmentation and object detection.
17
nnUNet_att_position_correction
354qpuchen/nnUNet_att_position_correction · Python
This is the official PyTorch code for the MICCAI 2023 STS Challenge (3D tooth segmentation from CBCT scans) by team sdkxd, which extends nn-UNet with axial attention and a positional correction module to clean up abnormal segmentation points.