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About Stacked Ensemble Learning For Malaria Detection
The document discusses using an ensemble deep learning technique to detect malaria parasites in blood smear images. It proposes combining the output layers of a ResNet50 model and a custom CNN model to take their average and make predictions. This ensemble model achieves high accuracy, specificity, sensitivity, and precision for malaria detection using small 64x64x3 input images. The total file size of this portable model is under 15MB, making it suitable for malaria detection even in remote areas with limited computational resources.
Detailed Information
Author: | ['Gopi Chand'] |
---|---|
Publication Year: | 2022 |
Pages: | 6 |
Language: | English |
Format: | |
Price: | FREE |
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