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Found 8 papers, 0 papers with code
Integrative Deep Learning Framework for Parkinson's Disease Early Detection using Gait Cycle Data Measured by Wearable Sensors: A CNN-GRU-GNN Approach
Efficient early diagnosis is paramount in addressing the complexities of Parkinson's disease because timely intervention can substantially mitigate symptom progression and improve patient outcomes.
An Explainable Deep Learning-Based Method For Schizophrenia Diagnosis Using Generative Data-Augmentation
In this study, we leverage a deep learning-based method for the automatic diagnosis of schizophrenia using EEG brain recordings.
UNFIS: A Novel Neuro-Fuzzy Inference System with Unstructured Fuzzy Rules for Classification
The performance of the proposed method is compared with some related previous approaches in some real-world classification problems.
A novel evolutionary-based neuro-fuzzy task scheduling approach to jointly optimize the main design challenges of heterogeneous MPSoCs
In this paper, an online task scheduling and mapping method based on a fuzzy neural network (FNN) learned by an evolutionary multi-objective algorithm (NSGA-II) to jointly optimize the main design challenges of heterogeneous MPSoCs is proposed.
Parkinson's Disease Diagnosis based on Gait Cycle Analysis Through an Interpretable Interval Type-2 Neuro-Fuzzy System
Therefore, experts can verify the decision made by the proposed method based on investigating the firing strength of interpretable fuzzy rules.
IT2CFNN: An Interval Type-2 Correlation-Aware Fuzzy Neural Network to Construct Non-Separable Fuzzy Rules with Uncertain and Adaptive Shapes for Nonlinear Function Approximation
Next, the new features are fed to a fuzzification layer using proposed interval type-2 fuzzy sets with adaptive shape.
Backpropagation-Free Learning Method for Correlated Fuzzy Neural Networks
This learning approach does not require backpropagating the output error to learn the premise parts' parameters.
A self-organizing fuzzy neural network for sequence learning
The proposed method is used to learn and reproduce different sequences simultaneously which is the novelty of this method.
