deepdumbo Goto Github PK

dsb3

A deep learning framework for lung cancer prediction built with Lasagne/Theano

dsb3tutorial

dsformer

Yao chao and Jin shuo and Liu meiqin and Ban xiaojuan

dsp_xilinx_ip

Some basic DSP algorithms implemented with xilinx IP cores with explanation, Verilog testbenches and modelling in Python

dtis

Predict DTIs

dtlp

Tensorflow code of CVPR 2021 paper "Learning Tensor Low-Rank Prior for Hyperspectral Image Reconstruction"

dtlp_pytorch

Pytorch code for CVPR 2021 paper: Learning Tensor Low-Rank Prior for Hyperspectral Image Reconstruction

duster

MRI DCE analysis

dvdnet

DVDnet: A Simple and Fast Network for Deep Video Denoising

dwimotioncorrect

Script to perform modified eddy_correct for b=3000 volumes.

dworklib

Useful utilities

dynamic-mri-reconstruction-using-cnn

In this we will impliment CNN architecture to reconstruct undersampled MRI sequences in keras platform

dynamic_rnn_conv_lstm

just a quick example of using the conv lstm in tensorflow as per https://github.com/tensorflow/tensorflow/pull/8891

dynamicradcinemri

Implementation of an iterative network for image reconstruction in 2D radial cardiac cine MRI.

ece3710

Lab Assignment for 3710

ece5760

labs for ECE 5760

echo-and-fir-filter-implementation-on-verilog-hdl

Verilog HDL implementation of an ECHO machine and an FIR filter that filters out a specific noise. More details provided in individual files. Download the project and run the main project file.

echoplanarreco

Matlab/ismrmrd script for single-shot EPI reconstruction

edaeprec

Enhanced Denoising Auto-Encoding Priors for Reconstruction

eddy-disruption

Prospective GIRF-based RF phase cycling to reduce eddy current-induced steady-state disruption in bSSFP imaging

eddymotion

Open-source eddy-current and head-motion correction for dMRI.

edsr-pytorch

PyTorch version of the paper 'Enhanced Deep Residual Networks for Single Image Super-Resolution' (CVPRW 2017)

ee324

Introduction to Digital Systems | WSU Fall 2017

eecs151_lab

elasticsearch-image-search

Stupid Experiments in Elasticsearch Image Search

elec391-final-project

Digital Communication System written in Verilog

emanet

The code for Expectation-Maximization Attention Networks for Semantic Segmentation (ICCV'2019 Oral)

emm-for-stock-prediction

We propose a model to analyze sentiment of online stock forum and use the information to predict stock volatility in the Chinese market. By generating a sentimental dictionary, we analyze the sentimental tendencies of each post as sentiment indicators. Such sentimental information will be fused with market data for prediction based on Recurrent Neural Networks (RNNs). We manually labeled the sentiment of forum post and make the data public available for research. Empirical evidence shows that 8 of the 10 stocks perform better with sentimental indicators.

emvd

Efficient Multi-Stage Video Denoising With Recurrent Spatio-Temporal Fusion. CVPR_2021.

encam