The Nelson Mandela African Institution of Science and Technology Malaria Dataset

These datasets have been developed to support a range of computer vision tasks, including image classification, object detection, and image segmentation. The dataset comprises both infected and uninfected blood smear images, encompassing both thick and thin smear slides. The effort to creating this datasets is motivated by the goal of advancing malaria diagnostic systems in Tanzania through the application of machine learning and deep learning techniques. By automating these diagnostic processes, we aim to mitigate subjective errors, reduce the time required for diagnosis, and alleviate the labor-intensive nature of traditional diagnostic methods.