RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
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Updated
Jun 1, 2019 - 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.
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
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.
This repo summarizes the tutorials, datasets, papers, codes and tools for speech separation and speaker extraction task. You are kindly invited to pull requests.
MATLAB implementations of Generative Adversarial Networks -- from GAN to Pixel2Pixel, CycleGAN
An analytical cost model evaluating DNN mappings (dataflows and tiling).
MatConvNet implementation for incorporating a 3D Morphable Model (3DMM) into a Spatial Transformer Network (STN)
⇨ 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…
PyTorch & Matlab code for the paper: CIE XYZ Net: Unprocessing Images for Low-Level Computer Vision Tasks (TPAMI 2021).
Deep Convolutional Framelets: A General Deep Learning Framework for Inverse Problems
This is a data-set for Human Activities & Gestures Recognition (HAGR) using the Channel State information (CSI) of IEEE 802.11n devices
💡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.
Simple MATLAB toolbox for deep learning network: Version 1.0.3
Code accompanying our ICVGIP 2016 paper
A perceptual weighting filter loss for DNN training in speech enhancement
k-Space Deep Learning for Accelerated MRI
MATLAB example of deep learning for image domain conversion
Synthetic exterior acoustic scattering data and sample parsing code.
Dataset and Evaluation Scripts for Obstacle Detection via Semantic Segmentation in a Marine Environment
Fuse the multiple images with different exposure
Deep Learning with Domain Adaptation for Accelerated Projection-Reconstruction MR