deep neuro-fuzzy networkHorse Herd OptimizationWhale Optimization AlgorithmThe most common life-threatening disease, acute lymphoblastic leukemia (ALL), can be lethal within a few weeks if untreated. The early detection and analysis of leukemia is a key dilemma in the field of disease diagnosis, ...
We leverage some of the advanced ConvNet architectures as a backbone-model of the proposed attention mapping network to build Cardio-XAttentionNet. The proposed model is trained on ChestX-Ray14, which is a publicly accessible chest X-ray dataset. The best single model achieves an overall ...
MB Narayanan,AK Ramesh,KSSA Gayathri - 《Journal of Intelligent & Fuzzy Systems Applications in Engineering & Technology》 被引量: 0发表: 2023年 Fake News Detection Using Deep Neuro-Fuzzy Network In this study, we introduce an innovative network architecture that synergizes fuzzy neural networks wit...
Jaya Honey Badger optimization-based deep neuro-fuzzy network structure for detection of (SARS-CoV) Covid-19 disease by using respiratory sound signals JHBO-enabled DNFN for Covid-19 detection: An effective Covid-19 detection technique is introduced based on hybrid optimization鈥揹riven deep learn...
The authors utilized a fuzzy neural network to provide robust classification results, and used two convolutional and two pooling layers to extract features. An optimized convolutional neural network model (ADECO-CNN) [83] is proposed for the COVID-19 detection in infected and not infected patients...
Finally, the deep neural network was compared with the logistic regression, support vector machine, and decision tree models. The datasets of 23 anaesthesia patients were used to assess the proposed method. Results The accuracies of the four models, in distinguishing the anaesthesia states, were ...
A deep neural network (DNN) based power control method is proposed, which aims at solving the non-convex optimization problem of maximizing the sum rate of a multi-user interference channel. Towards this end, we first present PCNet, which is a multi-layer fully connected neural network that ...
Zhou, M.et al.Epileptic seizure detection based on EEG signals and CNN.Front. Neuroinform.12, 95 (2018). ArticlePubMedPubMed CentralGoogle Scholar Chen, H., Song, Y. & Li, X. A deep learning framework for identifying children with ADHD using an EEG-based brain network.Neurocomputing356...
Where W is the weight matrix, and b is a bias term. In order to go beyond linear functions, we introduce a nonlinear hidden layer, resulting in the Multi Layer Perceptron. A feed-forward neural network with two hidden-layer has the form as : ...
Engin, M. "ECG beat classification using neuro-fuzzy network."Pattern Recognition Letters. Vol. 25, Number 15, 2004, pp.1715–1722. Goldberger A. L., L. A. N. Amaral, L. Glass, J. M. Hausdorff, P. Ch. Ivanov, R. G. Mark, J. E. Mietus, G. B. Moody, C.-...