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 …

UKSSL: underlying knowledge based semi-supervised learning for medical image classification

Z Ren, X Kong, Y Zhang, S Wang - IEEE Open Journal of …, 2023 - ieeexplore.ieee.org
Goal: Deep learning techniques have made significant progress in medical image analysis.
However, obtaining ground truth labels for unlabeled medical images is challenging as they …

RETRACTED ARTICLE: Peripheral Blood Smear Images Classification for Acute Lymphoblastic Leukemia Diagnosis with an Improved Convolutional Neural Network

E Özbay, FA Özbay, FS Gharehchopogh - Journal of Bionic Engineering, 2023 - Springer
The Editor-in-Chief has retracted this article because it overlaps significantly with a prior
publication with no common authors [1]. Specifically, images in Figs. 3 and 4 appear highly …

Classification of white blood cells using weighted optimized deformable convolutional neural networks

X Yao, K Sun, X Bu, C Zhao, Y ** - Artificial Cells, Nanomedicine …, 2021 - Taylor & Francis
Background Machine learning (ML) algorithms have been widely used in the classification of
white blood cells (WBCs). However, the performance of ML algorithms still needs to be …

Efficient deep feature extraction and classification for identifying defective photovoltaic module cells in Electroluminescence images

MY Demirci, N Beşli, A Gümüşçü - Expert Systems with Applications, 2021 - Elsevier
Electroluminescence (EL) imaging has become the standard test procedure for defect
detection throughout the production, installation and operation stages of solar modules …

Classification of white blood cell using convolution neural network

A Girdhar, H Kapur, V Kumar - Biomedical Signal Processing and Control, 2022 - Elsevier
The human immune system consists of White Blood Cells that are responsible for fighting of
disease pathogens. In the field of medical imagining, white blood cells is of great …

[PDF][PDF] RETRACTED: BCNet: A Novel Network for Blood Cell Classification

Z Zhu, S Lu, SH Wang, JM Górriz… - Frontiers in cell and …, 2022 - frontiersin.org
Aims: Most blood diseases, such as chronic anemia, leukemia (commonly known as blood
cancer), and hematopoietic dysfunction, are caused by environmental pollution …

An approach to classify white blood cells using convolutional neural network optimized by particle swarm optimization algorithm

K Balasubramanian, NP Ananthamoorthy… - Neural Computing and …, 2022 - Springer
Blood cell count is an important parameter in analysing a person's health condition. White
blood corpuscles (leukocytes) are responsible for deciding the immunity system of a person …

Classification of white blood cells: A comprehensive study using transfer learning based on convolutional neural networks

T Tamang, S Baral, MP Paing - Diagnostics, 2022 - mdpi.com
White blood cells (WBCs) in the human immune system defend against infection and protect
the body from external hazardous objects. They are comprised of neutrophils, eosinophils …

A comparison of automated classification techniques for image processing in video internet of things

RS Hawezi, FS Khoshaba, SW Kareem - Computers and Electrical …, 2022 - Elsevier
The counts of various types of white blood cells give vital information for identifying a variety
of ailments utilizing the video internet of things (VIoT). This technique needs to be automated …