A convolutional neural network approach for diabetic retinopathy classification
Diabetic Retinopathy (DR) is a kind of problem which affects diabetic patients, particularly
those at their age of working, and can result in vision impairment and possibly irreversible …
those at their age of working, and can result in vision impairment and possibly irreversible …
Liver disease prediction using machine learning classification techniques
Machine Learning is a process which is used to discover patterns in huge data/large data
set to enable decision, thereby allowing machines to go through a learning process (ie …
set to enable decision, thereby allowing machines to go through a learning process (ie …
A Neural Network Approach For Malware Classification
Malicious program is commonly known as malware, which is purposely designed to cause
problems in networks and harm in a variety of ways. Malware's primary goal is to disrupt …
problems in networks and harm in a variety of ways. Malware's primary goal is to disrupt …
Automatic epileptic seizure detection using MSA-DCNN and LSTM techniques with EEG signals
M Anita, AM Kowshalya - Expert Systems with Applications, 2024 - Elsevier
To identify epilepsy, Electroencephalography (EEG) is an important and common tool used
to study the electrical activity of the human brain. The machine learning-based classifier is …
to study the electrical activity of the human brain. The machine learning-based classifier is …
An automated deep learning enabled brain signal classification for epileptic seizure detection on complex measurement systems
J Escorcia-Gutierrez, K Beleno, J Jimenez-Cabas… - Measurement, 2022 - Elsevier
Recent advancements in machine learning and deep learning models find them helpful in
designing effective complex measurement systems. At the same time, examining the brain's …
designing effective complex measurement systems. At the same time, examining the brain's …
Software advancements in automatic epilepsy diagnosis and seizure detection: 10-year review
Epilepsy is a chronic neurological disorder that may be diagnosed and monitored using
routine diagnostic tests like Electroencephalography (EEG). However, manual introspection …
routine diagnostic tests like Electroencephalography (EEG). However, manual introspection …
Smart door locking system using IoT
The Internet of Things (IoT) has gained widespread attention among many research areas.
The modern automation has made the life more sophisticated and easier. An IoT based …
The modern automation has made the life more sophisticated and easier. An IoT based …
Toward extracting and exploiting generalizable knowledge of deep 2D transformations in computer vision
Existing deep learning models suffer from out-of-distribution (ood) performance drop in
computer vision tasks. In comparison, humans have a remarkable ability to interpret images …
computer vision tasks. In comparison, humans have a remarkable ability to interpret images …
SMARTSeiz: deep learning with attention mechanism for accurate seizure recognition in iot healthcare devices
The Internet of Things (IoT) is capable of controlling the healthcare monitoring system for
remote-based patients. Epilepsy, a chronic brain syndrome characterized by recurrent …
remote-based patients. Epilepsy, a chronic brain syndrome characterized by recurrent …
Application of transfer learning approach for diabetic retinopathy classification
Diabetes is a disorder of the metabolism caused by high glucose levels in the body.
Diabetes causes eye deficiency, also known as Diabetic Retinopathy (DR), which causes …
Diabetes causes eye deficiency, also known as Diabetic Retinopathy (DR), which causes …