Deep neural networks topic
Deep neural networks (DNNs) are a class of artificial neural networks (ANNs) that are deep in the sense that they have many layers of hidden units between the input and output layers. Deep neural networks are a type of deep learning, which is a type of machine learning. Deep neural networks are used in a variety of applications, including speech recognition, computer vision, and natural language processing. Deep neural networks are used in a variety of applications, including speech recognition, computer vision, and natural language processing.
realtime_object_detection
Plug and Play Real-Time Object Detection App with Tensorflow and OpenCV
Deep-Learning-in-Production
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
Great-Deep-Learning-Tutorials
A Great Collection of Deep Learning Tutorials and Repositories
Fastai-Deep-Learning-From-the-Foundations-TWiML-Study-Group
Review materials for the TWiML Study Group. Contains annotated versions of the original Jupyter noteboooks (look for names like *_jcat.ipynb ), slide decks from weekly Zoom meetups, etc.
CCML_Learning
This is the offical website for paper ''Category-consistent deep network learning for accurate vehicle logo recognition''
Adaptive-Gradient-Clipping
Minimal implementation of adaptive gradient clipping (https://arxiv.org/abs/2102.06171) in TensorFlow 2.
arc-pytorch
The first public PyTorch implementation of Attentive Recurrent Comparators
DBCNN-PyTorch
An experimental Pytorch implementation of Blind Image Quality Assessment Using A Deep Bilinear Convolutional Neural Network
UNIQUE
The repository for 'Uncertainty-aware blind image quality assessment in the laboratory and wild' and 'Learning to blindly assess image quality in the laboratory and wild'
tensorflow
An Open Source Machine Learning Framework for Everyone