A comprehensive survey of deep learning research on medical image analysis with focus on transfer learning
This survey aims to identify commonly used methods, datasets, future trends, knowledge
gaps, constraints, and limitations in the field to provide an overview of current solutions used …
gaps, constraints, and limitations in the field to provide an overview of current solutions used …
COVID-19 case recognition from chest CT images by deep learning, entropy-controlled firefly optimization, and parallel feature fusion
In healthcare, a multitude of data is collected from medical sensors and devices, such as X-
ray machines, magnetic resonance imaging, computed tomography (CT), and so on, that …
ray machines, magnetic resonance imaging, computed tomography (CT), and so on, that …
A deep survey on supervised learning based human detection and activity classification methods
Human detection and activity recognition is very important research area in the healthcare,
video surveillance, pedestrian detection, intelligent vehicle system and home care center …
video surveillance, pedestrian detection, intelligent vehicle system and home care center …
ANC: Attention network for COVID-19 explainable diagnosis based on convolutional block attention module
Y Zhang, X Zhang, W Zhu - Computer Modeling in Engineering …, 2021 - ingentaconnect.com
Aim: To diagnose COVID-19 more efficiently and more correctly, this study proposed a novel
attention network for COVID-19 (ANC). Methods: Two datasets were used in this study. An …
attention network for COVID-19 (ANC). Methods: Two datasets were used in this study. An …
[Retracted] A Rapid Artificial Intelligence‐Based Computer‐Aided Diagnosis System for COVID‐19 Classification from CT Images
The excessive number of COVID‐19 cases reported worldwide so far, supplemented by a
high rate of false alarms in its diagnosis using the conventional polymerase chain reaction …
high rate of false alarms in its diagnosis using the conventional polymerase chain reaction …
[PDF][PDF] Skin lesion segmentation and classification using conventional and deep learning based framework
Background: In medical image analysis, the diagnosis of skin lesions remains a challenging
task. Skin lesion is a common type of skin cancer that exists worldwide. Dermoscopy is one …
task. Skin lesion is a common type of skin cancer that exists worldwide. Dermoscopy is one …
[PDF][PDF] Multiclass Cucumber Leaf Diseases Recognition Using Best Feature Selection.
Agriculture is an important research area in the field of visual recognition by computers.
Plant diseases affect the quality and yields of agriculture. Early-stage identification of crop …
Plant diseases affect the quality and yields of agriculture. Early-stage identification of crop …
A hybrid CNN and ensemble model for COVID-19 lung infection detection on chest CT scans
COVID-19 is highly infectious and causes acute respiratory disease. Machine learning (ML)
and deep learning (DL) models are vital in detecting disease from computerized chest …
and deep learning (DL) models are vital in detecting disease from computerized chest …
[PDF][PDF] Pseudo zernike moment and deep stacked sparse autoencoder for COVID-19 diagnosis
(Aim) COVID-19 is an ongoing infectious disease. It has caused more than 107.45 m
confirmed cases and 2.35 m deaths till 11/Feb/2021. Traditional computer vision methods …
confirmed cases and 2.35 m deaths till 11/Feb/2021. Traditional computer vision methods …
A long short-term memory biomarker-based prediction framework for Alzheimer's disease
The early prediction of Alzheimer's disease (AD) can be vital for the endurance of patients
and establishes as an accommodating and facilitative factor for specialists. The proposed …
and establishes as an accommodating and facilitative factor for specialists. The proposed …