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.
models-comparison.pytorch
Code for the paper Benchmark Analysis of Representative Deep Neural Network Architectures
PipeCNN
An OpenCL-based FPGA Accelerator for Convolutional Neural Networks
DeepStream-Yolo
NVIDIA DeepStream SDK 7.0 / 6.4 / 6.3 / 6.2 / 6.1.1 / 6.1 / 6.0.1 / 6.0 / 5.1 implementation for YOLO models
keras-unet
Helper package with multiple U-Net implementations in Keras as well as useful utility tools helpful when working with image semantic segmentation tasks. This library and underlying tools come from mul...
Bender
Easily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood.
TengineKit
TengineKit - Free, Fast, Easy, Real-Time Face Detection & Face Landmarks & Face Attributes & Hand Detection & Hand Landmarks & Body Detection & Body Landmarks & Iris Landmarks & Yolov5 SDK On Mobile.
gans-in-action
Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks
vehicle_counting_tensorflow
:oncoming_automobile: "MORE THAN VEHICLE COUNTING!" This project provides prediction for speed, color and size of the vehicles with TensorFlow Object Counting API.
segan
Speech Enhancement Generative Adversarial Network in TensorFlow
PortaSpeech
PyTorch Implementation of PortaSpeech: Portable and High-Quality Generative Text-to-Speech