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k-space-deep-learning

k-Space Deep Learning for Accelerated MRI

k-space-transformer

kaggle-lung-cancer

Kaggle Data Science Bowl 2017

kaggle-rain

Winning solution to the Kaggle competition - How Much Did It Rain? II

kaggle_ndsb2

3rd place solution for the second kaggle national datascience bowl

kalman-and-bayesian-filters-in-python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

kapre

kapre: Keras Audio Preprocessors

kbr-denoising

code of KBR MSI denoising

kbr-tc-and-rpca

code of KBR_TC and KBR_RPCA

kcs-gsr

Group Sparse Representation for Kronecker Compressive Sensing, Image Process. Image Under. (IPIU) 2016

kcs-net

Deep Learning-Based Kronecker Compressive Imaging, ICCE-Asia 2018

kdrsdl

Code for Robust Kronecker-Decomposable Component Analysis (ICCV 2017)

keras

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

keras-dcgan

Keras implementation of Deep Convolutional Generative Adversarial Networks

keras-dualpathnetworks

Dual Path Networks for Keras 2.0+

keras-frcnn

keras-resnet

Keras package for deep residual networks

keras-rnn-timeseries

Keras-RNN-timeseries

keras-tf-super-resolution

Several approaches for bumping up image resolution with NNs (GANs)

kerasr

DeepLearning using Keras with R

keras_stft_layer

Do STFT in Keras

kernel-principal-component-analysis-kernel-pca-

In the field of multivariate statistics, kernel principal component analysis (kernel PCA) [1] is an extension of principal component analysis (PCA) using techniques of kernel methods. Using a kernel, the originally linear operations of PCA are performed in a reproducing kernel Hilbert space.

kernel-principal-component-analysis-kpca

KPCA for dimensionality reduction, feature extraction , fault detection, and fault diagnosis

kgcnn

code of KGCNN

kids_rsfmri_motion

kronecker-based-cs-recovery

Kronecker technique for improving quality of the signal in compressive sensing recovery

kspace-coil-combination-of-noncartesian-mrsi-data

kspace.deeplearning.mri

k-Space Deep Learning for Accelerated MRI Reconstruction

kspace_demo

Simulation of MRI epi acquisition

kspace_precond

Scripts to reproduce experiments for k-space preconditioning