Deep Learning Architectures for PM2.5 and Visibility Predictions

Facing the severe air pollution phenomenon in urban areas and the subsequent low visibility event in airports, it is urgent to conduct air quality and visibility predictions to better reflect their changing trends. However, the variations of PM2.5 and visibility involve complicated physical and chemical processes, which make their accurate...

Automated malaria diagnosis using convolutional neural networks in an on-field setting: The analysis of low quality smartphone based microscope images

This study focuses on automated malaria diagnosis in low quality blood smear images, captured by a low-cost smartphone based microscope system. The aim is to localize and classify the healthy and infected erythrocytes (red blood cells) in order to evaluate the parasitaemia in an infected blood smear. Due to the lower quality of the smartphone...