Semantic Explanation for Malaria Diagnosis: Comparing Human and Machine Generated Annotations for Plasmodium Species and Life-Stage Features
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Goal: Accurate detection of malaria parasites using convolutional neural networks (CNNs) relies heavily on the quality of training annotations, yet creating quality annotations is both time-consuming and difficult to scale in high-burden, resource-limited sett... ...
