[HTML][HTML] Computer-Aided Diagnosis Systems for Automatic Malaria Parasite Detection and Classification: A Systematic Review
Malaria is a disease that affects millions of people worldwide with a consistent mortality rate.
The light microscope examination is the gold standard for detecting infection by malaria …
The light microscope examination is the gold standard for detecting infection by malaria …
Domain adaptive object detection via balancing between self-training and adversarial learning
Deep learning based object detectors struggle generalizing to a new target domain bearing
significant variations in object and background. Most current methods align domains by …
significant variations in object and background. Most current methods align domains by …
Improving Single Domain-Generalized Object Detection: A Focus on Diversification and Alignment
In this work we tackle the problem of domain generalization for object detection specifically
focusing on the scenario where only a single source domain is available. We propose an …
focusing on the scenario where only a single source domain is available. We propose an …
[HTML][HTML] Enhancing medical image analysis with unsupervised domain adaptation approach across microscopes and magnifications
In the domain of medical image analysis, deep learning models are heralding a revolution,
especially in detecting complex and nuanced features characteristic of diseases like tumors …
especially in detecting complex and nuanced features characteristic of diseases like tumors …
Bio-net dataset: AI-based diagnostic solutions using peripheral blood smear images
Peripheral blood smear examination is one of the basic steps in the evaluation of different
blood cells. It is a confirmatory step after an automated complete blood count analysis …
blood cells. It is a confirmatory step after an automated complete blood count analysis …
A combination of optimized threshold and deep learning-based approach to improve malaria detection and segmentation on PlasmoID dataset
HA Nugroho, R Nurfauzi - FACETS, 2023 - facetsjournal.com
Malaria is a life-threatening parasitic disease transmitted to humans by infected female
Anopheles mosquitoes. Early and accurate diagnosis is crucial to reduce the high mortality …
Anopheles mosquitoes. Early and accurate diagnosis is crucial to reduce the high mortality …
A deep architecture based on attention mechanisms for effective end-to-end detection of early and mature malaria parasites
Malaria is a severe infectious disease caused by the Plasmodium parasite. The early and
accurate detection of this disease is crucial to reducing the number of deaths it causes …
accurate detection of this disease is crucial to reducing the number of deaths it causes …
Identifying out of distribution samples for skin cancer and malaria images
Deep neural networks have shown promising results in disease detection and classification
using medical image data. However, they still suffer from the challenges of handling real …
using medical image data. However, they still suffer from the challenges of handling real …
Automated web-based malaria detection system with machine learning and deep learning techniques
AG Taye, S Yemane, E Negash, Y Minwuyelet… - arXiv preprint arXiv …, 2024 - arxiv.org
Malaria parasites pose a significant global health burden, causing widespread suffering and
mortality. Detecting malaria infection accurately is crucial for effective treatment and control …
mortality. Detecting malaria infection accurately is crucial for effective treatment and control …
YOLO-PAM: Parasite-Attention-Based Model for Efficient Malaria Detection
Malaria is a potentially fatal infectious disease caused by the Plasmodium parasite. The
mortality rate can be significantly reduced if the condition is diagnosed and treated early …
mortality rate can be significantly reduced if the condition is diagnosed and treated early …