R-CNN was proposed by Ross Girshick et al. in 2014 to deal with the problem of efficient object localization in object detection. It changed the object detection field fundamentally. By leveraging ...

Abstract: 3D object detection, leveraging depth information to deliver spatial attributes of targets including location, orientation, and size, is advancing rapidly in autonomous driving and robotics.

Abstract: In order to solve the problem of poor bicycle and pedestrian detection under sparse point cloud conditions in autonomous driving, an improved Voxel-RCNN algorithm is proposed to optimize the ...

To propose a non-contrast CT-based algorithm for automated and accurate detection of pancreatic lesions at a low cost. With Faster RCNN as the benchmark model, an advanced Faster RCNN (aFaster RCNN) ...

ing at the problem of inaccurate fruit recognition and fruit diameter detection in persimmon inspection process, this research proposes a novel persimmon accurate recognition and fruit diameter ...

pred_class = [COCO_INSTANCE_CATEGORY_NAMES[i] for i in list(pred[0]['labels'].numpy())] pred_boxes = [[(i[0], i[1]), (i[2], i[3])] for i in list(pred[0]['boxes ...