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zhangyuan's Projects

conv_arithmetic icon conv_arithmetic

A technical report on convolution arithmetic in the context of deep learning

cyclegan-tensorflow icon cyclegan-tensorflow

Tensorflow implementation for learning an image-to-image translation without input-output pairs. https://arxiv.org/pdf/1703.10593.pdf

danet icon danet

Dual Attention Network for Scene Segmentation (CVPR2019)

dcgan-tensorflow icon dcgan-tensorflow

A tensorflow implementation of Deep Convolutional Generative Adversarial Networks

dcgan_code icon dcgan_code

Deep Convolutional Generative Adversarial Networks

deep-goggle icon deep-goggle

Source code for "Understanding Deep Image Representations by Inverting Them", CVPR 2015

deeplearning-500-questions icon deeplearning-500-questions

深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,50余万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系[email protected] 版权所有,违权必究 Tan 2018.06

deeplearntoolbox icon deeplearntoolbox

Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.

deeptam icon deeptam

DeepTAM: Deep Tracking and Mapping https://lmb.informatik.uni-freiburg.de/people/zhouh/deeptam/

dfusmc icon dfusmc

Depth from Uncalibrated Small Motion Clip

distiller icon distiller

Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://nervanasystems.github.io/distiller

dpt icon dpt

Dense Prediction Transformers

dss icon dss

code for "Deeply supervised salient object detection with short connections" published in CVPR 2017

dss-pytorch icon dss-pytorch

Pytorch implement of Deeply Supervised Salient Object Detection with Short Connection

edge_detection_framework icon edge_detection_framework

Pytorch implementation of different edge detection networks, such as Holistically-Nested Edge Detection and PixelNet

emdl icon emdl

Embedded and mobile deep learning research resources

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