Yongsong.H (yongsongH)

yongsongH

Geek Repo

Company:IIC Lab, Tohoku University

Home Page:https://hyongsong.work

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Yongsong.H's repositories

attend-and-rectify

Pytorch code for the ECCV paper "Attend and rectify"

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attention-transfer

Improving Convolutional Networks via Attention Transfer (ICLR 2017)

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AUDASC

Adversarial Unsupervised Domain Adaptation for Acoustic Scene Classification

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CNN_Visualization

Implementation of visualization techniques for CNN in Caffe (t-sne, DeconvNet, Image occlusions)

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ELM-pytorch

Extreme Learning Machine implemented in Pytorch

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ELM-tensorflow

Extreme Learning Machine with TensorFlow

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ESPCN-TensorFlow

An implementation of the Efficient Sub-Pixel Convolutional Neural Network in TensorFlow

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image-captioning

Image captioning models "show and tell" + "show, attend and tell" in PyTorch

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intentions

Do deep reinforcement learning agents model intentions?

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Mask-RCNN

A PyTorch implementation of the architecture of Mask RCNN, serves as an introduction to working with PyTorch

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MRCNN-for-Scene-Classification

Pytorch implementation of MRCNN for SceneClassification( Knowledge Guided Disambiguation for Large-Scale Scene Classification with Multi-Resolution CNNs)

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mx-maskrcnn

An MXNet implementation of Mask R-CNN

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places365

The Places365-CNNs for Scene Classification

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PyTorch-SRGAN

A modern PyTorch implementation of SRGAN

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resnet-1k-layers

Deep Residual Networks with 1K Layers

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scene-baseline

PyTorch baseline for AI challenger Scene classification

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SceneClassification

This project is to use deep learning to auto classify the scene images with limited amount of training images.

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SceneClassify

AI场景分类竞赛

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Single-Image-Super-Resolution-SISR

A list of resources for example-based single image super-resolution

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Speech_Emotion_Recognition_DNN-ELM

Implementation of Speech Emotion Recognition using DNN-ELM

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SRGAN_Wasserstein

Apply Waseerstein GAN into SRGAN, a deep learning super resolution model

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subpixel

subpixel: A subpixel convnet for super resolution with Tensorflow

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Super_Resolution_with_CNNs_and_GANs

Image Super-Resolution Using SRCNN, DRRN, SRGAN, CGAN in Pytorch

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TensorFlow-ESPCN

Super resolution with Tensorflow

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video-super-resolution

Video super resolution implemented in Pytorch

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WassersteinGAN-1

Tensorflow Wasserstein GAN implementation with TFRecord data format. WGAN, WGAN-GP (gradient penalty), DCGAN and showing example usage with CelebA dataset.

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Xception-PyTorch

A PyTorch implementation of Xception: Deep Learning with Depthwise Separable Convolutions

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