-
Chapter and Conference Paper
Automated Malaria Cells Detection from Blood Smears Under Severe Class Imbalance via Importance-Aware Balanced Group Softmax
Malaria is one of the main threats to global health. Manual examination of thick and thin blood smears is the current gold standard for diagnosing malaria. However, it is of extremely low throughput and suscep...
-
Chapter and Conference Paper
Memory-Efficient Automatic Kidney and Tumor Segmentation Based on Non-local Context Guided 3D U-Net
Automatic kidney and tumor segmentation from CT volumes is essential for clinical diagnosis and surgery planning. However, it is still a very challenging problem as kidney and tumor usually exhibit various sca...
-
Chapter and Conference Paper
RVSeg-Net: An Efficient Feature Pyramid Cascade Network for Retinal Vessel Segmentation
Accurate retinal vessel segmentation plays a critical role in the diagnosis of many relevant diseases. However, it remains a challenging task due to (1) the great scale variation of retinal vessels, (2) the ex...
-
Chapter and Conference Paper
PolypSeg: An Efficient Context-Aware Network for Polyp Segmentation from Colonoscopy Videos
Polyp segmentation from colonoscopy videos is of great importance for improving the quantitative analysis of colon cancer. However, it remains a challenging task due to (1) the large size and shape variation o...
-
Chapter and Conference Paper
An Artificial Neural Network for Solving Quadratic Zero-One Programming Problems
This paper proposes a neurodynamic approach for solving the quadratic zero-one programming problem with linear constraints. Based on the basic idea of the Scholtes’ relaxation scheme, the original quadratic ze...