This is the repo that will be used to store the code used for the Intel / IBACs AI technical workshop hosted at the University of Connecticut.
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Updated
Apr 24, 2018 - Python
This is the repo that will be used to store the code used for the Intel / IBACs AI technical workshop hosted at the University of Connecticut.
Model for translating speech to text. This is similar to using amazon alexa amongst many other products
DeepFake ECG generator based on 1D Convoloutional Neural Networks
1-dimensional convolution implementation using C++ and CUDA
Speech Emotion Recognition using 1D and 2D Convolutional Neural Networks
Complete project of predicting the weather condition using Deep Learning
Movie ratings prediction
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
Bengali Newses are classified in six catagories. This is done by first extracting the semantics of Bengali words using word2vec. Then using those semantics, all the news are classified. Bengali NLP resources are not very rich compared to other languages. This is a complete project that includes Bengali word embedding, data cleaning using word st…
This repository contains Convolutional Neural Networks implemented from scratch.
Public repository associated with: Assessing The Effect of Various Sampling Frequency and Double Soft F1-loss in Multi-Label Classification of 12-Lead ECGs
A repository related to a master thesis in electronics, informatics and technology. Title: "Comparing Cardiological and Algorithm-Based ECG Interpretation in Athletes: Can Artificial Intelligence Improve the Algorithms?"
a CNN that used word embeddings from GloVe to classify toxic comments
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.
[Re] Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL, N. Strodthoff, P. Wagner, T. Schaeffter, and W. Samek,
Anti-hydrogen detection using CNNs from ASACUSA experiment
ECG classification using public data and state-of-the-art 1D CNN models. This work is based on George Moody Challenge 2020
Set of 2D & 1D CNN models to classify images of handwritten numbers from the MNIST dataset using Keras.
1DConvNet applied to room occupancy detection based on data from several environment sensors. Data courtesy of the UCI Machine Learning Repository.
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