Complete project of predicting the weather condition using Deep Learning

Audio processing by using pytorch 1D convolution network

This repository contains Convolutional Neural Networks implemented from scratch.

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

Public repository associated with: "Using deep convolutional neural networks to predict patients age based on ECGs from an independent test cohort"

This repository is associated with Multi-Label ECG Classification Using Convolutional Neural Networks in a Classifier Chain

This work is the preliminary experiments leading to the publication: Towards Invariant Soft Biometrics from Electrocardiograms

Public repository associated with: "MemoryInception: Predicting Neurological Recovery from EEG Using Recurrent Inceptions"

[Re] Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL, N. Strodthoff, P. Wagner, T. Schaeffter, and W. Samek,

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

Public repository associated with: "honocardiogram classification using 1-dimensional inception time convolutional neural network"

A version of the YOLOv3 network capable of handling 1D data inputs.

NLP-FinHeadlines-MoodTracker is a NLP project utilising sentiment analysis on financial news headlines. It employs a combination of CNN and LSTM layers to predict sentiment (positive, negative, neutral). The model incorporates an embedding layer, 1D convolution, max pooling, bidirectional LSTM, dropout, and dense layer for sentiment classification.

A pytorch package for non-negative matrix factorization.

Public repository associated with: Assessing The Effect of Various Sampling Frequency and Double Soft F1-loss in Multi-Label Classification of 12-Lead ECGs

Speech Emotion Recognition using 1D and 2D Convolutional Neural Networks

On-the-fly spectrogram generation

Classification models 1D Zoo - Keras and TF.Keras

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

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)