A tutorial for Speech Enhancement researchers and practitioners. The purpose of this repo is to organize the world’s resources for speech enhancement and make them universally accessible and useful.
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Updated
Dec 1, 2020 - MATLAB
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.
A tutorial for Speech Enhancement researchers and practitioners. The purpose of this repo is to organize the world’s resources for speech enhancement and make them universally accessible and useful.
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
This repo summarizes the tutorials, datasets, papers, codes and tools for speech separation and speaker extraction task. You are kindly invited to pull requests.
MatConvNet implementation for incorporating a 3D Morphable Model (3DMM) into a Spatial Transformer Network (STN)
MATLAB implementations of Generative Adversarial Networks -- from GAN to Pixel2Pixel, CycleGAN
An analytical cost model evaluating DNN mappings (dataflows and tiling).
PyTorch & Matlab code for the paper: CIE XYZ Net: Unprocessing Images for Low-Level Computer Vision Tasks (TPAMI 2021).
This is a data-set for Human Activities & Gestures Recognition (HAGR) using the Channel State information (CSI) of IEEE 802.11n devices
Dataset and Evaluation Scripts for Obstacle Detection via Semantic Segmentation in a Marine Environment
⇨ The Speaker Recognition System consists of two phases, Feature Extraction and Recognition. ⇨ In the Extraction phase, the Speaker's voice is recorded and typical number of features are extracted to form a model. ⇨ During the Recognition phase, a speech sample is compared against a previously created voice print stored in the database. ⇨ The hi…
k-Space Deep Learning for Accelerated MRI
Deep Convolutional Framelets: A General Deep Learning Framework for Inverse Problems
A perceptual weighting filter loss for DNN training in speech enhancement
💡This repository contains all of the lecture exercises of Machine Learning course by Andrew Ng, Stanford University @ Coursera. All are implemented by myself and in MATLAB/Octave.
MATLAB example of deep learning for image domain conversion
Synthetic exterior acoustic scattering data and sample parsing code.
Simple MATLAB toolbox for deep learning network: Version 1.0.3
Code accompanying our ICVGIP 2016 paper
Vehicle Detection based on Faster R-CNN
Implementation of an LSTM network in MATLAB that predicts future power consumptions of 3 zones in Tetuan City.