154 citations · 342 across the 14 of their papers we have counts for
14 papers
The Role of Natural Language Understanding in Multimodal Video-Based Dengue Diagnosis
Danial Sharifrazi, Saadat Behzadi, Julakha Jahan Jui +5
Detecting infection-related behavioral changes in mosquitoes from video data is challenging because mosquitoes are small, move rapidly and irregularly, and are affected by environm…
A Hybrid Framework of Vision Transformer and Gated Recurrent Unit for Detection of Mosquito Diseases
Danial Sharifrazi, Saadat Behzadi, Nouman Javed +3
Identifying dengue virus-infected mosquitoes from control mosquitoes is a major challenge in analyzing mosquito locomotion behavior due to the small size and complexity of the vide…
SSI-GAN: Semi-Supervised Swin-Inspired Generative Adversarial Networks for Neuronal Spike Classification
Danial Sharifrazi, Nouman Javed, Mojtaba Mohammadi +5
Mosquitos are the main transmissive agents of arboviral diseases. Manual classification of their neuronal spike patterns is very labor-intensive and expensive. Most available deep…
A Lightweight and Robust Framework for Real-Time Colorectal Polyp Detection Using LOF-Based Preprocessing and YOLO-v11n
Saadat Behzadi, Danial Sharifrazi, Bita Mesbahzadeh +2
Objectives: Timely and accurate detection of colorectal polyps plays a crucial role in diagnosing and preventing colorectal cancer, a major cause of mortality worldwide. This study…
Brain Ageing Prediction using Isolation Forest Technique and Residual Neural Network (ResNet)
Saadat Behzadi, Danial Sharifrazi, Roohallah Alizadehsani +2
Brain aging is a complex and dynamic process, leading to functional and structural changes in the brain. These changes could lead to the increased risk of neurodegenerative disease…
Functional Classification of Spiking Signal Data Using Artificial Intelligence Techniques: A Review
Danial Sharifrazi, Nouman Javed, Javad Hassannataj Joloudari +5
Human brain neuron activities are incredibly significant nowadays. Neuronal behavior is assessed by analyzing signal data such as electroencephalography (EEG), which can offer scie…
Automated detection of Zika and dengue in Aedes aegypti using neural spiking analysis
Danial Sharifrazi, Nouman Javed, Roohallah Alizadehsani +3
Mosquito-borne diseases present considerable risks to the health of both animals and humans. Aedes aegypti mosquitoes are the primary vectors for numerous medically important virus…
AI Framework for Early Diagnosis of Coronary Artery Disease: An Integration of Borderline SMOTE, Autoencoders and Convolutional Neural Networks Approach
Elham Nasarian, Danial Sharifrazi, Saman Mohsenirad +2
The accuracy of coronary artery disease (CAD) diagnosis is dependent on a variety of factors, including demographic, symptom, and medical examination, ECG, and echocardiography dat…
Accurate Discharge Coefficient Prediction of Streamlined Weirs by Coupling Linear Regression and Deep Convolutional Gated Recurrent Unit
Weibin Chen, Danial Sharifrazi, Guoxi Liang +3
Streamlined weirs which are a nature-inspired type of weir have gained tremendous attention among hydraulic engineers, mainly owing to their established performance with high disch…
FCM-DNN: diagnosing coronary artery disease by deep accuracy Fuzzy C-Means clustering model
Javad Hassannataj Joloudari, Hamid Saadatfar, Mohammad GhasemiGol +6
Cardiovascular disease is one of the most challenging diseases in middle-aged and older people, which causes high mortality. Coronary artery disease (CAD) is known as a common card…
Time series forecasting of new cases and new deaths rate for COVID-19 using deep learning methods
Nooshin Ayoobi, Danial Sharifrazi, Roohallah Alizadehsani +9
The first known case of Coronavirus disease 2019 (COVID-19) was identified in December 2019. It has spread worldwide, leading to an ongoing pandemic, imposed restrictions and costs…
Combining a Convolutional Neural Network with Autoencoders to Predict the Survival Chance of COVID-19 Patients
Fahime Khozeimeh, Danial Sharifrazi, Navid Hoseini Izadi +10
COVID-19 has caused many deaths worldwide. The automation of the diagnosis of this virus is highly desired. Convolutional neural networks (CNNs) have shown outstanding classificati…
Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images
Danial Sharifrazi, Roohallah Alizadehsani, Mohamad Roshanzamir +13
The coronavirus (COVID-19) is currently the most common contagious disease which is prevalent all over the world. The main challenge of this disease is the primary diagnosis to pre…
Uncertainty-Aware Semi-Supervised Method Using Large Unlabeled and Limited Labeled COVID-19 Data
Roohallah Alizadehsani, Danial Sharifrazi, Navid Hoseini Izadi +11
The new coronavirus has caused more than one million deaths and continues to spread rapidly. This virus targets the lungs, causing respiratory distress which can be mild or severe.…