Работы, цитирующие эту работу

Работ: 4

Работа: PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes

1. The RGB-D Triathlon: Towards Agile Visual Toolboxes for Robots

   Fabio Cermelli, Massimiliano Mancini, Elisa Ricci +1

   ПрепринтAdvanced Neural Network Applications2019Цитирований: 0

   ABIABI:AkademIndex/openalex/2019.preprint.000031

2. Hardware Acceleration of Monte-Carlo Sampling for Energy Efficient Robust Robot Manipulation

   Yanqi Liu, Giuseppe Calderoni, R. Iris Bahar

   ПрепринтRobot Manipulation and LearningarXiv (Cornell University)2020Цитирований: 0

   ABIABI:AkademIndex/openalex/2020.preprint.000041

3. A deep learning framework for real‐time 3D model registration in robot‐assisted laparoscopic surgery

   Erica Padovan, Giorgia Marullo, Leonardo Tanzi +4

   СтатьяSurgical Simulation and TrainingInternational Journal of Medical Robotics and Computer Assisted Surgery2022Цитирований: 0

   ABIABI:AkademIndex/openalex/2022.article.000123

4. Experimental Verification of a Monocular CNN-Based Pose Estimation Algorithm for the SROC Mission

   Antonio D'Ortona, Lucrezia Lovaglio, Marco Visca +2

   ПрепринтSpace Satellite Systems and ControlResearch Square2026Цитирований: 0

   ABIABI:AkademIndex/openalex/2026.preprint.000085