Search Results for author:
Found 4 papers, 0 papers with code
Contextual Embedding Learning to Enhance 2D Networks for Volumetric Image Segmentation
Accordingly, we propose a contextual embedding learning approach to facilitate 2D CNNs capturing spatial information properly.
STOPNet: Multiview-based 6-DoF Suction Detection for Transparent Objects on Production Lines
In this work, we present STOPNet, a framework for 6-DoF object suction detection on production lines, with a focus on but not limited to transparent objects, which is an important and challenging problem in robotic systems and modern industry.
Dual-View Selective Instance Segmentation Network for Unstained Live Adherent Cells in Differential Interference Contrast Images
In this study, we developed a novel deep-learning algorithm called dual-view selective instance segmentation network (DVSISN) for segmenting unstained adherent cells in differential interference contrast (DIC) images.
Stereo Dense Scene Reconstruction and Accurate Localization for Learning-Based Navigation of Laparoscope in Minimally Invasive Surgery
Then, we develop a dense visual reconstruction algorithm to represent the scene by surfels, estimate the laparoscope poses and fuse the depth maps into a unified reference coordinate for tissue reconstruction.
