no code implementations • 27 Jan 2023 • Soroush Hashemifar, Abdolreza Marefat, Javad Hassannataj Joloudari, Hamid Hassanpour
To the best of our knowledge, FRA is the first method that shifts its focus towards manipulating the face embeddings generated by any face representation learning algorithm to create new embeddings representing the same identity and facial emotion but with an altered posture.
no code implementations • 4 Nov 2022 • Javad Hassannataj Joloudari, Sadiq Hussain, Mohammad Ali Nematollahi, Rouhollah Bagheri, Fatemeh Fazl, Roohallah Alizadehsani, Reza Lashgari, Ashis Talukder
The superiority of BERT models over other deep models in sentiment analysis is evident and can be concluded from the comparison of the various research studies mentioned in this article.
no code implementations • 1 Sep 2022 • Javad Hassannataj Joloudari, Abdolreza Marefat, Mohammad Ali Nematollahi, Solomon Sunday Oyelere, Sadiq Hussain
Imbalanced Data (ID) is a problem that deters Machine Learning (ML) models for achieving satisfactory results.
no code implementations • 23 Mar 2022 • Javad Hassannataj Joloudari, Sanaz Mojrian, Hamid Saadatfar, Issa Nodehi, Fatemeh Fazl, Sahar Khanjani Shirkharkolaie, Roohallah Alizadehsani, H M Dipu Kabir, Ru-San Tan, U Rajendra Acharya
In this paper, according to the latest scientific achievements, a comprehensive literature study (CLS) on artificial intelligence methods based on resource allocation optimization without considering auction-based methods in various computing environments are provided such as cloud computing, Vehicular Fog Computing, wireless, IoT, vehicular networks, 5G networks, vehicular cloud architecture, machine-to-machine communication(M2M), Train-to-Train(T2T) communication network, Peer-to-Peer(P2P) network.
no code implementations • 9 Feb 2022 • Javad Hassannataj Joloudari, Hamid Saadatfar, Mohammad GhasemiGol, Roohallah Alizadehsani, Zahra Alizadeh Sani, Fereshteh Hasanzadeh, Edris Hassannataj, Danial Sharifrazi, Zulkefli Mansor
First, the labeled dataset is applied to the NN and DNN to create the NN and DNN models.
no code implementations • 23 Jul 2021 • Javad Hassannataj Joloudari, Faezeh Azizi, Mohammad Ali Nematollahi, Roohallah Alizadehsani, Edris Hassannataj, Amir Mosavi
One of the alternative solutions is the use of machine learning-based patterns for CAD diagnosis.
no code implementations • 5 Jul 2021 • Javad Hassannataj Joloudari, Sanaz Mojrian, Issa Nodehi, Amir Mashmool, Zeynab Kiani Zadegan, Sahar Khanjani Shirkharkolaie, Roohallah Alizadehsani, Tahereh Tamadon, Samiyeh Khosravi, Mitra Akbari Kohnehshari, Edris Hassannatajjeloudari, Danial Sharifrazi, Amir Mosavi, Hui Wen Loh, Ru-San Tan, U Rajendra Acharya
Artificial intelligence-based methods can be utilized to screen for or diagnose MI automatically using ECG signals.
no code implementations • 18 Apr 2021 • Fahime Khozeimeh, Danial Sharifrazi, Navid Hoseini Izadi, Javad Hassannataj Joloudari, Afshin Shoeibi, Roohallah Alizadehsani, Juan M. Gorriz, Sadiq Hussain, Zahra Alizadeh Sani, Hossein Moosaei, Abbas Khosravi, Saeid Nahavandi, Sheikh Mohammed Shariful Islam
To show that clinical data can be used for COVID-19 survival chance prediction, the CNN-AE was compared with multiple pre-trained deep models that were tuned based on CT images.
no code implementations • 13 Feb 2021 • 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
In this study, a fusion of convolutional neural network (CNN), support vector machine (SVM), and Sobel filter is proposed to detect COVID-19 using X-ray images.
no code implementations • 12 Feb 2021 • Roohallah Alizadehsani, Danial Sharifrazi, Navid Hoseini Izadi, Javad Hassannataj Joloudari, Afshin Shoeibi, Juan M. Gorriz, Sadiq Hussain, Juan E. Arco, Zahra Alizadeh Sani, Fahime Khozeimeh, Abbas Khosravi, Saeid Nahavandi, Sheikh Mohammed Shariful Islam, U Rajendra Acharya
Our system is capable of learning from a mixture of limited labeled and unlabeled data where supervised learners fail due to a lack of sufficient amount of labeled data.
no code implementations • 19 Sep 2020 • Javad Hassannataj Joloudari, Mojtaba Haderbadi, Amir Mashmool, Mohammad GhasemiGol, Shahab S., Amir Mosavi
One of the most common and important destructive attacks on the victim system is Advanced Persistent Threat (APT)-attack.
no code implementations • 16 Jan 2020 • Javad Hassannataj Joloudari, Edris Hassannataj Joloudari, Hamid Saadatfar, Mohammad GhasemiGol, Seyyed Mohammad Razavi, Amir Mosavi, Narjes Nabipour, Shahaboddin Shamshirband, Laszlo Nadai
Among the vast number of heart diseases, the coronary artery disease (CAD) is considered as a common cardiovascular disease with a high death rate.
no code implementations • 29 Oct 2019 • Sanaz Mojrian, Gergo Pinter, Javad Hassannataj Joloudari, Imre Felde, Narjes Nabipour, Laszlo Nadai, Amir Mosavi
The performance of the proposed model is further compared with a linear-SVM model.