Deep Transfer Graph Convolutional Network

We develop a novel deep learning approach for multi-stage malaria parasites recognition in blood smear images using Deep Transfer Graph Convolutional Network (DTGCN). And this work is the first application of GCN on multi-stage malaria parasites recognition in blood smear images. The proposed DTGCN model is based on unsupervised learning by transferring knowledge learnt from source images that contain the discriminative morphology character-istics of multi-stage malaria parasites. These transferred information guarantees the effectiveness on the target parasites recognition.