Author:Javad Hassannataj Joloudari

Publications
EasyChair Preprint no. 10394
EasyChair Preprint no. 9633
EasyChair Preprint no. 9282
EasyChair Preprint no. 7645
EasyChair Preprint no. 7829
EasyChair Preprint no. 6771
EasyChair Preprint no. 6173
EasyChair Preprint no. 6048
EasyChair Preprint no. 6330
EasyChair Preprint no. 2467
EasyChair Preprint no. 1824

Keyphrases

Artificial Intelligence2, Autoencoder, BERT, breast cancer, breast cancer dataset, Breast Cancer Detection, cancer mass, Cloud Computing, Confusion Matrix, Convolutional Neural Networks, coronary artery disease2, coronary artery disease diagnosis, Coronary Heart Disease, COVID-19, COVID-19 Diagnosis, cross validation technique, CT scan images, Data Mining, Data Mining Technique, Deep Convolutional Neural Network, deep learning4, Deep Neural Network2, developed country, diagnosis, Edge Computing, Electrocardiogram, ELM model, elm rbf model, emotion recognition, epithelial cell size, evaluation criterion, expert system, Extended Cohen-Kanade (CK+) Dataset, Extreme Learning Machine, Extreme Learning Machine (ELM), Face Embeddings, face recognition, Face Representation Learning, facial expression recognition, Facial Pose Reconstruction, feature extraction, first module, fold cross, fuzzy c-means clustering, Fuzzy Linguistic Variable, fuzzy rule, fuzzy system, Genetic Algorithm, Health Informatics, Heart Disease, hybrid machine learning, image analysis, Internet of Things, Latent Space Data Augmentation, linguistic variable, machine learning5, Malaria diagnosis, Malignant breast cancer, MobileViT2, multilayer fuzzy expert system, Myocardial Infarction Disease, Natural Language Processing, negative rate, neural network2, Optical Flow Algorithm, prediction, Predictive Features, Radial Basis Function, Radial Basis Function (RBF), Reinforcement Learning, resource allocation, rmse r2 mape model, Sentiment Analysis, Support Vector Machine2, Support Vector Machine (SVM), Tweets, Vision Transformers2, Wisconsin Dataset.