An important logistics application of robotics involves manipulators that pick-and-place
objects placed in warehouse shelves. A critical aspect of this task corresponds to detecting …

We present a novel and efficient approach to estimate 6D object poses of known objects in
complex scenes represented by point clouds. Our approach is based on the well-known …

This paper presents a new method for estimating normals on unorganized point clouds that
preserves sharp features. It is based on a robust version of the Randomized Hough …

Normal estimation in point clouds is a crucial first step for numerous algorithms, from surface
reconstruction and scene understanding to rendering. A recurrent issue when estimating …

Предложен миварный подход к распознаванию образов. Приведен обзор
необходимого инструментария для перехода от обработки двухмерных изображений к …

In this paper, we present an object pose estimation algorithm exploiting both depth and color
information. While many approaches assume that a target region is cleanly segmented from …

Purpose The study aimed to predict acute radiation esophagitis (ARE) with grade≥ 2 for
patients with locally advanced lung cancer (LALC) treated with intensity-modulated radiation …

Purpose: This study investigates the impact of lung function on radiation pneumonitis
prediction using a dual-omics analysis method. Methods: We retrospectively collected data …

Simple Summary Acute radiation pneumonitis (ARP) is one of the common radiation
toxicities in patients with non-small-cell lung cancer (NSCLC) treated by radiotherapy. The …

We present an object pose estimation approach exploiting both geometric depth and
photometric color information available from an RGB-D sensor. In contrast to various efforts …