A comprehensive survey of recent trends in deep learning for digital images augmentation

NE Khalifa, M Loey, S Mirjalili - Artificial Intelligence Review, 2022 - Springer
Deep learning proved its efficiency in many fields of computer science such as computer
vision, image classifications, object detection, image segmentation, and more. Deep …

A review on traditional machine learning and deep learning models for WBCs classification in blood smear images

S Khan, M Sajjad, T Hussain, A Ullah, AS Imran - Ieee Access, 2020 - ieeexplore.ieee.org
In computer vision, traditional machine learning (TML) and deep learning (DL) methods
have significantly contributed to the advancements of medical image analysis (MIA) by …

Fighting against COVID-19: A novel deep learning model based on YOLO-v2 with ResNet-50 for medical face mask detection

M Loey, G Manogaran, MHN Taha… - Sustainable cities and …, 2021 - Elsevier
Deep learning has shown tremendous potential in many real-life applications in different
domains. One of these potentials is object detection. Recent object detection which is based …

A hybrid deep transfer learning model with machine learning methods for face mask detection in the era of the COVID-19 pandemic

M Loey, G Manogaran, MHN Taha, NEM Khalifa - Measurement, 2021 - Elsevier
The coronavirus COVID-19 pandemic is causing a global health crisis. One of the effective
protection methods is wearing a face mask in public areas according to the World Health …

A deep learning model (ALNet) for the diagnosis of acute leukaemia lineage using peripheral blood cell images

L Boldú, A Merino, A Acevedo, A Molina… - Computer Methods and …, 2021 - Elsevier
Background and objectives Morphological differentiation among blasts circulating in blood
in acute leukaemia is challenging. Artificial intelligence decision support systems hold …

Blood cancer prediction using leukemia microarray gene data and hybrid logistic vector trees model

V Rupapara, F Rustam, W Aljedaani, HF Shahzad… - Scientific reports, 2022 - nature.com
Blood cancer has been a growing concern during the last decade and requires early
diagnosis to start proper treatment. The diagnosis process is costly and time-consuming …

[Retracted] Explainable AI in Diagnosing and Anticipating Leukemia Using Transfer Learning Method

WH Abir, MF Uddin, FR Khanam, T Tazin… - Computational …, 2022 - Wiley Online Library
White blood cells (WBCs) are blood cells that fight infections and diseases as a part of the
immune system. They are also known as “defender cells.” But the imbalance in the number …

A systematic review on acute leukemia detection using deep learning techniques

R Raina, NK Gondhi, Chaahat, D Singh, M Kaur… - … Methods in Engineering, 2023 - Springer
Acute leukemia is a cancer that starts in the bone marrow and is characterized by an
abnormal growth of white blood cells. It is a disease that affects people all over the world …

BO-ALLCNN: Bayesian-based optimized CNN for acute lymphoblastic leukemia detection in microscopic blood smear images

G Atteia, AA Alhussan, NA Samee - Sensors, 2022 - mdpi.com
Acute lymphoblastic leukemia (ALL) is a deadly cancer characterized by aberrant
accumulation of immature lymphocytes in the blood or bone marrow. Effective treatment of …

A customized efficient deep learning model for the diagnosis of acute leukemia cells based on lymphocyte and monocyte images

S Ansari, AH Navin, AB Sangar, JV Gharamaleki… - Electronics, 2023 - mdpi.com
The production of blood cells is affected by leukemia, a type of bone marrow cancer or blood
cancer. Deoxyribonucleic acid (DNA) is related to immature cells, particularly white cells …