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Danial Sharifrazi
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2020 – today
- 2024
- [j3]Danial Sharifrazi
, Nouman Javed
Automated detection of Zika and dengue in Aedes aegypti using neural spiking analysis: A machine learning approach. Biomed. Signal Process. Control. 96: 106594 (2024) - [i10]Danial Sharifrazi, Nouman Javed, Javad Hassannataj Joloudari, Roohallah Alizadehsani, Prasad N. Paradkar, Ru San Tan, U. Rajendra Acharya, Asim Bhatti:
Functional Classification of Spiking Signal Data Using Artificial Intelligence Techniques: A Review. CoRR abs/2409.17516 (2024) - 2023
- [i9]Elham Nasarian, Danial Sharifrazi, Saman Mohsenirad, Kwok Tsui, Roohallah Alizadehsani:
AI Framework for Early Diagnosis of Coronary Artery Disease: An Integration of Borderline SMOTE, Autoencoders and Convolutional Neural Networks Approach. CoRR abs/2308.15339 (2023) - [i8]Danial Sharifrazi, Nouman Javed
Automated detection of Zika and dengue in Aedes aegypti using neural spiking analysis. CoRR abs/2312.08654 (2023) - 2022
- [i7]Javad Hassannataj Joloudari, Hamid Saadatfar, Mohammad GhasemiGol, Roohallah Alizadehsani, Zahra Alizadeh Sani, Fereshteh Hasanzadeh, Edris Hassannataj, Danial Sharifrazi, Zulkefli Mansor:
FCM-DNN: diagnosing coronary artery disease by deep accuracy Fuzzy C-Means clustering model. CoRR abs/2202.04645 (2022) - [i6]Weibin Chen, Danial Sharifrazi, Guoxi Liang, Shahab S. Band, Kwok-Wing Chau, Amir Mosavi:
Accurate Discharge Coefficient Prediction of Streamlined Weirs by Coupling Linear Regression and Deep Convolutional Gated Recurrent Unit. CoRR abs/2204.05476 (2022) - 2021
- [j2]Danial Sharifrazi, Roohallah Alizadehsani
Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images. Biomed. Signal Process. Control. 68: 102622 (2021) - [j1]Roohallah Alizadehsani
Uncertainty-Aware Semi-Supervised Method Using Large Unlabeled and Limited Labeled COVID-19 Data. ACM Trans. Multim. Comput. Commun. Appl. 17(3s): 104:1-104:24 (2021) - [i5]Roohallah Alizadehsani
Uncertainty-Aware Semi-supervised Method using Large Unlabelled and Limited Labeled COVID-19 Data. CoRR abs/2102.06388 (2021) - [i4]Danial Sharifrazi, Roohallah Alizadehsani, Mohamad Roshanzamir, Javad Hassannataj Joloudari, Afshin Shoeibi, Mahboobeh Jafari, Sadiq Hussain, Zahra Alizadeh Sani, Fereshteh Hasanzadeh, Fahime Khozeimeh, Abbas Khosravi, Saeid Nahavandi, Maryam Panahiazar, Assef Zare, Sheikh Mohammed Shariful Islam, U. Rajendra Acharya:
Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images. CoRR abs/2102.06883 (2021) - [i3]Fahime Khozeimeh, Danial Sharifrazi, Navid Hosseini Izadi, Javad Hassannataj Joloudari
CNN AE: Convolution Neural Network combined with Autoencoder approach to detect survival chance of COVID 19 patients. CoRR abs/2104.08954 (2021) - [i2]Nooshin Ayoobi, Danial Sharifrazi, Roohallah Alizadehsani, Afshin Shoeibi, Juan Manuel Górriz, Hossein Moosaei
Time Series Forecasting of New Cases and New Deaths Rate for COVID-19 using Deep Learning Methods. CoRR abs/2104.15007 (2021) - [i1]Javad Hassannataj Joloudari, Sanaz Mojrian, Issa Nodehi, Amir Mashmool, Zeynab Kiani Zadegan, Sahar Khanjani Shirkharkolaie, Tahereh Tamadon, Samiyeh Khosravi, Mitra Akbari, Edris Hassannataj, Roohallah Alizadehsani
A Survey of Applications of Artificial Intelligence for Myocardial Infarction Disease Diagnosis. CoRR abs/2107.06179 (2021)
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