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Found 13 papers, 0 papers with code
ALIVE: A Low-Cost Interactive Vaccine Storage Environment Module ensuring easy portability and remote tracking of operational logistics to the last mile
Despite the frugal nature of development, the system promises significant benefits, including reduced vaccine loss and remote monitoring advantages.
M3BUNet: Mobile Mean Max UNet for Pancreas Segmentation on CT-Scans
Segmenting organs in CT scan images is a necessary process for multiple downstream medical image analysis tasks.
COVID-19 Detection System: A Comparative Analysis of System Performance Based on Acoustic Features of Cough Audio Signals
A wide range of respiratory diseases, such as cold and flu, asthma, and COVID-19, affect people's daily lives worldwide.
Classification of sleep stages from EEG, EOG and EMG signals by SSNet
The performance of our proposed model is evaluated by using two public datasets Sleep-EDF Expanded dataset and ISRUC-Sleep dataset.
#REVAL: a semantic evaluation framework for hashtag recommendation
Our experiments of the proposed framework on three large datasets show that #REval gave more meaningful hashtag synonyms for hashtag recommendation evaluation.
Patient Independent Interictal Epileptiform Discharge Detection
This is implemented using raw EEG data, sourced from Temple University Hospital's EEG Epilepsy Corpus, and is found to outperform the current state of the art model for IED detection across the same dataset.
MP-SeizNet: A Multi-Path CNN Bi-LSTM Network for Seizure-Type Classification Using EEG
The EEG data is fed to our proposed model in two different representations.
Evaluating BERT-based Pre-training Language Models for Detecting Misinformation
The result of the proposed technique has been compared with the state-of-the-art techniques on the same datasets.
Wavelet-Based Multi-Class Seizure Type Classification System
Epilepsy is one of the most common brain diseases that affect more than 1\% of the world's population.
BERT based classification system for detecting rumours on Twitter
These approaches rely on feature extraction to obtain both content and context features from the text of tweets to distinguish rumours and non-rumours.
Estimating galaxy masses from kinematics of globular cluster systems: a new method based on deep learning
Then we use the CNN to predict the total masses of galaxies (i. e., test the CNN) for the totally unknown dataset that is not used in training the CNN.
Automatic detection of abnormal EEG signals using wavelet feature extraction and gradient boosting decision tree
In this paper, we present an automatic binary classification framework for brain signals in multichannel EEG recordings.
Hit ratio: An Evaluation Metric for Hashtag Recommendation
A comparison of hit ratio with the classical evaluation metrics reveals their limitations.
