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Found 9 papers, 1 papers with code
Designing the Architecture of a Convolutional Neural Network Automatically for Diabetic Retinopathy Diagnosis
However, the existing CNN-based methods use either pre-trained CNN models or a brute force approach to design new CNN models, which are not customized to the complexity of fundus images.
A Deep Learning-Based Unified Framework for Red Lesions Detection on Retinal Fundus Images
For this system, we introduced a new ROIs candidates generation method for large red lesions on fundus images; it is based on blood vessel segmentation and morphological operations, and reduces the computational complexity, and enhances the detection accuracy by generating a small number of potential candidates.
An Efficient Intelligent System for the Classification of Electroencephalography (EEG) Brain Signals using Nuclear Features for Human Cognitive Tasks
The nuclear features from frontal brain region gave the 100% prediction accuracy.
Automatic Emotion Recognition (AER) System based on Two-Level Ensemble of Lightweight Deep CNN Models
A DL model involves a large number of learnable parameters, and its training needs a large dataset of EEG signals, which is difficult to acquire for AER problem.
Eigen Values Features for the Classification of Brain Signals corresponding to 2D and 3D Educational Contents
Eigenvalues features extracted from topomaps images are given to K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) classifiers, in order to identify the states of the brain related to incorrect and correct answers.
Alignment-Free Cross-Sensor Fingerprint Matching based on the Co-Occurrence of Ridge Orientations and Gabor-HoG Descriptor
The existing automatic fingerprint verification methods are designed to work under the assumption that the same sensor is installed for enrollment and authentication (regular matching).
Deep Learning based Computer-Aided Diagnosis Systems for Diabetic Retinopathy: A Survey
A computer-aided diagnosis (CAD) system based on retinal fundus images is an efficient and effective method for early DR diagnosis and assisting experts.
ConvSRC: SmartPhone based Periocular Recognition using Deep Convolutional Neural Network and Sparsity Augmented Collaborative Representation
Smartphone based periocular recognition has gained significant attention from biometric research community because of the limitations of biometric modalities like face, iris etc.
An Automated System for Epilepsy Detection using EEG Brain Signals based on Deep Learning Approach
Epilepsy is a neurological disorder and for its detection, encephalography (EEG) is a commonly used clinical approach.
