wind222's repositories

awesome-rnn

Recurrent Neural Network - A curated list of resources dedicated to RNN

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bayesian-video-super-resolution

Bayesian video super-resolution

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BRCN

A unofficial implementation of paper method that 'Bidirectional Recurrent Convolutional Networks for Multi-Frame Super-Resolution'

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caffe-lowlevel

Project for paper "Learning Recursive Filters for Low-Level Vision via a Hybrid Neural Network", ECCV 2016

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Codes-for-Lane-Detection

Codes for the CNN-based lane detection models

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ConvLSTM

Spatio-temporal video autoencoder with convolutional LSTMs

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Convolution-in-RNN

Convolution Neural Network in RNN (GRU、LSTM、etc)

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cs231n.github.io

Public facing notes page

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deep_cnn

Deep convolution neural network project with TensorFlow

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DeepFace

Face analysis mainly based on Caffe. At this time, face analysis tasks like detection, alignment and recognition have been done.

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DenseNet

DenseNet implementation in Keras

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DenseNetCaffe

Caffe code for Densely Connected Convolutional Networks (DenseNets)

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DnCNN

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

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Face-Hallucination-For-Video-Surveillance-Graduation-Project-

a novel face hallucination algorithm to synthesize a high-resolution face image from several low-resolution input face images. Face hallucination normally uses twomodels: a global parametricmodel which synthesizes the global face shapes from eigenfaces, and a local parametric model which enhances the local high frequency details.We follow a similar process to develop a robust face hallucination algorithm. First, we obtain eigenfaces from a number of low resolution face images segmented from a video sequence using a face tracking algorithm. Then we compute the difference between an interpolated low-resolution face and a mean face, and use this difference as the query to retrieve an approximate sparse eigenface representation. The eigenfaces are combined using the coefficients obtained from the sparse representation and added into the interpolated low-resolution face. In this way, the global shape of the interpolated low resolution face can be successfully enhanced. Second, we improve the example-based super-resolution method for local high frequency information enhancement. Our proposed algorithm uses the Approximate Nearest Neighbors (ANN) search method to find a number of nearest neighbors for a stack of queries, instead of finding the exact match for each low frequency patch. Median filtering is used to remove the noise from the nearest neighbors in order to enhance the signal. Our proposed algorithm uses a sparse representation and the ANN method to enhance both global face shape and local high frequency information while greatly improving the processing speed, as confirmed empirically.

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Face-Hallucination-of-Facial-Components

FH by Neighbor Embedding Facial Components

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FRRN

Full Resolution Residual Networks for Semantic Image Segmentation

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FudanOCR

A toolbox of scene text detection and recognition

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Generative-Adversarial-Network-Demo

Generative Adversarial Network Demo for Fresh Machine Learning #2

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generative-adversial

image generation via GANs

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keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano or TensorFlow.

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LSTM-and-maxlayer-for-SNV-based-phenotype-prediction

Source code used in my MSc thesis "LSTM and convolutional neural networks for SNV-based phenotype prediction Long Short-Term Memory and convolutional neural networks for SNV-based phenotype prediction"

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mxnet-ssd

MXNet port of SSD: Single Shot MultiBox Object Detector. Reimplementation of https://github.com/weiliu89/caffe/tree/ssd

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neural-enhance

Super Resolution for images using deep learning.

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Photo-Realistic-Super-Resoluton

Torch Implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"

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rcnn

Recurrent & convolutional neural network modules

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SN-GAN

pyTorch implementation of Spectral Normalization for Generative Adversarial Networks

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SR-LicensePlate

This is a repository about the paper A.N. Vicente and H. Pedrini: "A Learning-Based Single-Image Super-Resolution Method for Very Low Quality License Plate Images"

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SRGAN

A tensorflow implemenation of Christian et al's SRGAN(super-resolution generative adversarial network)

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