3 accepted papers
Thanks to the development of convolutional neural networks (CNNs), researchers have proposed lots of effective semantic segmentation models. However, there are still two problems disturbing researchers, one of which is objects misidentification on the image level and another one is poor performance…
The chest X-ray is one of the most commonly available radiological examinations for diagnosing lung diseases. This task remains a major challenge due to 1) the shortage of accurate annotations for chest X-ray examinations, 2) the diversity of lesion areas on X-rays from different thoracic disease an…
This paper aims to achieve high-accuracy 3D object detection, in which we propose a novel Spatial-Channel Attention Network (SCANet), a two-stage detector that takes both LIDAR point clouds and RGB images as input to generate 3D object estimates. The first stage is a 3D region proposal network (RPN)…