Audio processing by using pytorch 1D convolution network

Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine

A pytorch package for non-negative matrix factorization.

SeqNet: Code for the RA-L (ICRA) 2021 paper "SeqNet: Learning Descriptors for Sequence-Based Hierarchical Place Recognition"

[深度应用]·首届中国心电智能大赛初赛开源Baseline（基于Keras val_acc: 0.88）

This repository provides the code used to create the results presented in "Global canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles".

This is a CNN based model which aims to automatically classify the ECG signals of a normal patient vs. a patient with AF and has been trained to achieve up to 93.33% validation accuracy.

Models supported: ResNet, ResNetV2, SE-ResNet, ResNeXt, SE-ResNeXt [layers: 18, 34, 50, 101, 152] (1D and 2D versions with DEMO for Classification and Regression).

Models Supported: Inception [v1, v2, v3, v4], SE-Inception, Inception_ResNet [v1, v2], SE-Inception_ResNet (1D and 2D version with DEMO for Classification and Regression)

In this work we propose two postprocessing approaches applying convolutional neural networks (CNNs) either in the time domain or the cepstral domain to enhance the coded speech without any modification of the codecs. The time domain approach follows an end-to-end fashion, while the cepstral domain approach uses analysis-synthesis with cepstral d…

Public repository associated with: Convolutional Neural Network and Rule-Based Algorithms for Classifying 12-lead ECGs

1D convolutional neural networks for activity recognition in python.

Classification models 1D Zoo - Keras and TF.Keras

Models Supported: VGG11, VGG13, VGG16, VGG16_v2, VGG19 (1D and 2D versions with DEMO for Classification and Regression).

Predict blood pressure (systolic and diastolic) rythm from ECG and pulse oximeter signals

Set of 1D CNN models to classify sound clips from the Urban Sound Classification dataset using Keras and Librosa

IDH and TERTp mutation classification in gliomas using 1D-CNN with MRS data.

用Tensorflow2.0進行外匯收盤價預測, 使用LSTM, 1d-CNN, Seq2Seq

Play The Piano With Deep Learning 用深度学习弹钢琴 2019-5-22

1-D convolution implementation using Python and CUDA