Nov 26, 2021 � We present a dataset to further the research on malaria microscopy over the low-cost microscopes at low magnification. Our large-scale dataset�...
(f) The patch in 1000x view. (g) Images captured with all three lenses. (h) Patches extracted. (e) Moving the patch in. 1000x view field.
We present a dataset to further the research on malaria microscopy over the low-cost microscopes at low magnification. Our large-scale dataset consists of�...
To achieve low-cost and efficient malaria detection using deep learn- ing, it is vital to collect malaria data from the low-cost mi- croscope and at lower�...
We present a dataset to further the research on malaria microscopy over the low-cost microscopes at low magnification. Our large-scale dataset consists of�...
A large-scale dataset of images of blood-smear slides from several malaria-infected patients, collected through micro-scopes at two different cost spectrums�...
Towards Low-Cost and Efficient Malaria Detection
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We present a dataset to further the research on malaria microscopy over low-cost microscopes at low magnification.
Nov 26, 2021 � We present a dataset to further the research on malariamicroscopy over the low-cost microscopes at low magnification. Our large-scaledataset�...
This paper presents a methodology for automatic diagnosis of malaria using computer vision techniques combined with artificial intelligence. We had obtained an�...
Jun 10, 2024 � In this paper, EfficientNet, a deep learning-based approach for detecting Malaria, is proposed that uses red blood cell images.