Review on COVID‐19 diagnosis models based on machine learning and deep learning approaches
COVID‐19 is the disease evoked by a new breed of coronavirus called the severe acute
respiratory syndrome coronavirus 2 (SARS‐CoV‐2). Recently, COVID‐19 has become a …
respiratory syndrome coronavirus 2 (SARS‐CoV‐2). Recently, COVID‐19 has become a …
Artificial intelligence-based hybrid deep learning models for image classification: The first narrative review
Background Artificial intelligence (AI) has served humanity in many applications since its
inception. Currently, it dominates the imaging field—in particular, image classification. The …
inception. Currently, it dominates the imaging field—in particular, image classification. The …
A survey on deep learning-based real-time crowd anomaly detection for secure distributed video surveillance
K Rezaee, SM Rezakhani, MR Khosravi… - Personal and Ubiquitous …, 2024 - Springer
Fast and automated recognizing of abnormal behaviors in crowded scenes is significantly
effective in increasing public security. The traditional procedure of recognizing abnormalities …
effective in increasing public security. The traditional procedure of recognizing abnormalities …
A hybrid deep transfer learning-based approach for Parkinson's disease classification in surface electromyography signals
K Rezaee, S Savarkar, X Yu, J Zhang - Biomedical Signal Processing and …, 2022 - Elsevier
Parkinson's disease (PD) is known as a rampant neurodegenerative disorder, which has
afflicted approximately 10 million people throughout the world. Surface Electromyography …
afflicted approximately 10 million people throughout the world. Surface Electromyography …
Convolutional neural network and its pretrained models for image classification and object detection: A survey
At present, in the age of computers and automation of services, deep learning (DL)
technology, mainly the subset of machine learning (ML) and artificial intelligence (AI), is …
technology, mainly the subset of machine learning (ML) and artificial intelligence (AI), is …
An autonomous UAV-assisted distance-aware crowd sensing platform using deep ShuffleNet transfer learning
K Rezaee, SJ Mousavirad, MR Khosravi… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Autonomous unmanned aerial vehicles (UAVs) are essential for detecting and tracking
specific events, such as automatic navigation. The intelligent monitoring of people's social …
specific events, such as automatic navigation. The intelligent monitoring of people's social …
Deep learning‐based microarray cancer classification and ensemble gene selection approach
Malignancies and diseases of various genetic origins can be diagnosed and classified with
microarray data. There are many obstacles to overcome due to the large size of the gene …
microarray data. There are many obstacles to overcome due to the large size of the gene …
Ensemble-based multi-tissue classification approach of colorectal cancer histology images using a novel hybrid deep learning framework
M Khazaee Fadafen, K Rezaee - Scientific Reports, 2023 - nature.com
Colorectal cancer (CRC) is the second leading cause of cancer death in the world, so digital
pathology is essential for assessing prognosis. Due to the increasing resolution and quantity …
pathology is essential for assessing prognosis. Due to the increasing resolution and quantity …
A CNN‐Based Chest Infection Diagnostic Model: A Multistage Multiclass Isolated and Developed Transfer Learning Framework
In 2019, a deadly coronaviral infection (COVID‐19) that infected millions of people globally
was detected in China. This fatal virus affects the respiratory system and currently spreads to …
was detected in China. This fatal virus affects the respiratory system and currently spreads to …
A trustworthy and explainable framework for benchmarking hybrid deep learning models based on chest X-ray analysis in CAD systems
Evaluating the trustworthiness of deep learning-based computer-aided diagnosis (CAD)
systems is challenging. There is a need to optimize trust and performance in model …
systems is challenging. There is a need to optimize trust and performance in model …