There are 112 repositories under convolutional-neural-networks topic.
A MNIST-like fashion product database. Benchmark :point_down:
Best Practices, code samples, and documentation for Computer Vision.
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
Techniques for deep learning with satellite & aerial imagery
all kinds of text classification models and more with deep learning
VIP cheatsheets for Stanford's CS 230 Deep Learning
T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced researchers will find it fascinating as well.
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.
A best practice for tensorflow project template architecture.
This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.
Code examples for new APIs of iOS 10.
🧠💬 Articles I wrote about machine learning, archived from MachineCurve.com.
PyTorch implementation of Super SloMo by Jiang et al.
Simple and comprehensive tutorials in TensorFlow
深度学习与PyTorch入门实战视频教程 配套源代码和PPT
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
Udacity Self-Driving Car Engineer Nanodegree projects.
TensorFlow Tutorials
Image Deblurring using Generative Adversarial Networks
Minkowski Engine is an auto-diff neural network library for high-dimensional sparse tensors
Türkiye'de yapılan derin öğrenme (deep learning) ve makine öğrenmesi (machine learning) çalışmalarının derlendiği sayfa.
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
A simple interface for editing natural photos with generative neural networks.
Convolutional Neural Networks to predict the aesthetic and technical quality of images.
Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation
Text Classification Algorithms: A Survey
Computer Vision library for human-computer interaction. It implements Head Pose and Gaze Direction Estimation Using Convolutional Neural Networks, Skin Detection through Backprojection, Motion Detection and Tracking, Saliency Map.