[HTML][HTML] Application of deep learning and machine learning models to improve healthcare in sub-Saharan Africa: Emerging opportunities, trends and implications
E Mbunge, J Batani - Telematics and Informatics Reports, 2023 - Elsevier
Deep learning and machine learning techniques present unmatched opportunities to
improve healthcare in sub-Saharan Africa (SSA). However, there is a paucity of literature on …
improve healthcare in sub-Saharan Africa (SSA). However, there is a paucity of literature on …
The laboratory diagnosis of malaria: a focus on the diagnostic assays in non-endemic areas
A Calderaro, G Piccolo, C Chezzi - International Journal of Molecular …, 2024 - mdpi.com
Even if malaria is rare in Europe, it is a medical emergency and programs for its control
should ensure both an early diagnosis and a prompt treatment within 24–48 h from the onset …
should ensure both an early diagnosis and a prompt treatment within 24–48 h from the onset …
An Efficient VGG19 Framework for Malaria Detection in Blood Cell Images
Malaria diagnosis by microscopy is a method for identifying malaria using cell pictures. In
order to do this, a blood sample must be examined under a microscope to determine …
order to do this, a blood sample must be examined under a microscope to determine …
MWA-MNN: Multi-patch wavelet attention memristive neural network for image restoration
Adverse weather conditions can severely reduce the image quality captured by outdoor
imaging devices. However, most existing image restoration algorithms are designed for …
imaging devices. However, most existing image restoration algorithms are designed for …
An optimised YOLOv4 deep learning model for efficient malarial cell detection in thin blood smear images
Background Malaria is a serious public health concern worldwide. Early and accurate
diagnosis is essential for controlling the disease's spread and avoiding severe health …
diagnosis is essential for controlling the disease's spread and avoiding severe health …
[PDF][PDF] Deep learning-based computer assisted detection techniques for malaria parasite using blood smear images
Malaria remains a significant global health concern, impacting various regions worldwide.
Achieving effective treatment and reducing mortality rates hinges on early and accurate …
Achieving effective treatment and reducing mortality rates hinges on early and accurate …
A hybrid artistic model using deepy-dream model and multiple convolutional neural networks architectures
The significant increase in drug abuse cases prompts developers to investigate techniques
that mimic the hallucinations imagined by addicts and abusers, in addition to the increasing …
that mimic the hallucinations imagined by addicts and abusers, in addition to the increasing …
[HTML][HTML] Vision-enhanced Peg-in-Hole for automotive body parts using semantic image segmentation and object detection
Artificial Intelligence (AI) is an enabling technology in the context of Industry 4.0. In
particular, the automotive sector is among those who can benefit most of the use of AI in …
particular, the automotive sector is among those who can benefit most of the use of AI in …
Efficient deep learning-based approach for malaria detection using red blood cell smears
Malaria is an extremely malignant disease and is caused by the bites of infected female
mosquitoes. This disease is not only infectious among humans, but among animals as well …
mosquitoes. This disease is not only infectious among humans, but among animals as well …
Landmark: Language-guided representation enhancement framework for scene graph generation
X Chang, T Wang, S Cai, C Sun - Applied Intelligence, 2023 - Springer
Scene graph generation (SGG) is a sophisticated task that suffers from both complex visual
features and the long-tail problem. Recently, various unbiased strategies have been …
features and the long-tail problem. Recently, various unbiased strategies have been …