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Deep learning and machine learning for Malaria detection: overview, challenges and future directions
Public health initiatives must be made using evidence-based decision-making to have the
greatest impact. Machine learning algorithms are created to gather, store, process, and …
greatest impact. Machine learning algorithms are created to gather, store, process, and …
Artificial intelligence-based approaches for detection and classification of different classes of malaria parasites using microscopic images: a systematic review
Artificial Intelligence has played an essential role in detecting malaria, which aims to reduce
the involvement of any human microscopist in order provide an accurate diagnosis with …
the involvement of any human microscopist in order provide an accurate diagnosis with …
Accurate classification of white blood cells by coupling pre-trained ResNet and DenseNet with SCAM mechanism
Background Via counting the different kinds of white blood cells (WBCs), a good quantitative
description of a person's health status is obtained, thus forming the critical aspects for the …
description of a person's health status is obtained, thus forming the critical aspects for the …
An efficient multi-level convolutional neural network approach for white blood cells classification
The evaluation of white blood cells is essential to assess the quality of the human immune
system; however, the assessment of the blood smear depends on the pathologist's …
system; however, the assessment of the blood smear depends on the pathologist's …
[PDF][PDF] A Step Towards Automated Haematology: DL Models for Blood Cell Detection and Classification
INTRODUCTION: Deep Learning has significantly impacted various domains, including
medical imaging and diagnostics, by enabling accurate classification tasks. This research …
medical imaging and diagnostics, by enabling accurate classification tasks. This research …
Classification of microscopic peripheral blood cell images using multibranch lightweight CNN-based model
H Fırat - Neural Computing and Applications, 2024 - Springer
White blood cells (WBC), which are human peripheral blood cells, are the most significant
part of the immune system that defends the body against microorganisms. Modifications in …
part of the immune system that defends the body against microorganisms. Modifications in …
Classification of white blood cell using convolution neural network
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 …
disease pathogens. In the field of medical imagining, white blood cells is of great …
Leukocyte classification based on feature selection using extra trees classifier: Atransfer learning approach
D Baby, SJ Devaraj, J Hemanth - Turkish Journal of Electrical …, 2021 - journals.tubitak.gov.tr
The criticality of investigating the white blood cell (WBC) count cannot be underestimated, as
white blood cells are an important component of the body's defence system. From hel** to …
white blood cells are an important component of the body's defence system. From hel** to …
WBC image classification and generative models based on convolutional neural network
Background Computer-aided methods for analyzing white blood cells (WBC) are popular
due to the complexity of the manual alternatives. Recent works have shown highly accurate …
due to the complexity of the manual alternatives. Recent works have shown highly accurate …
Classification of white blood cells (leucocytes) from blood smear imagery using machine and deep learning models: A global sco** review
Machine learning (ML) and deep learning (DL) models are being increasingly employed for
medical imagery analyses, with both approaches used to enhance the accuracy of …
medical imagery analyses, with both approaches used to enhance the accuracy of …