Unsupervised learning method for shape matching templates based on gradient saliency estimation-Reference-Cited by-同舟云学术

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Unsupervised learning method for shape matching templates based on gradient saliency estimation

Published:2022-12-05 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)
language:
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Author:

Li Sicong¹,Zhu Feng¹,Wu Qingxiao¹

Affiliation:

1. Chinese Academy of Sciences,Key Laboratory of Opto- Electronic Information Processing,Shenyang,China,110016

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10011626/10011636/10011963.pdf?arnumber=10011963

Reference12 articles.

1. A high-precision positioning algorithm of alignment mark for wafer bonding;lu;Chinese Journal of Scientific Instrument,2021

2. Wheel model identification based on shape recognition and texture filtering;cheng;Chinese Journal of Scientific Instrument,2017

3. Fast Object Localization and Pose Etimation in Heavy Clutter for Robotic Bin Picking;liu;IJRR,2012

4. Occlusion, clutter, and illumination invariant object recognition;steger;Int Arch Photogrammetry Remote Sensing,2002

5. An Improved Adaptive Background Mixture Model for Real-Time Tracking with Shadow Detection;kaewtrakulpong;AVBS,2001

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