Object Description Using Visual and Tactile Data-Reference-Cited by-同舟云学术

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Object Description Using Visual and Tactile Data

Published:2022 Issue: Volume:10 Page:54525-54536
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Zhang Peng¹^ORCID,Zhou Maohui²,Shan Dongri²^ORCID,Chen Zhenxue³^ORCID,Wang Xiaofang¹

Affiliation:

1. School of Electrical Engineering and Automation, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China

2. School of Mechanical Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China

3. School of Control Science and Engineering, Shandong University, Jinan, China

Funder

Project of Shandong Provincial Major Scientific and Technological Innovation

Project of 20 Policies to Facilitate Scientific Research at Jinan Colleges

Natural Science Foundation of Shandong Province of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09774426.pdf?arnumber=9774426

Reference29 articles.

1. Accuracy and speed of material categorization in real-world images

2. Material recognition in the wild with the Materials in Context Database

3. Describing Textures in the Wild

4. Haptic Zero-Shot Learning: Recognition of objects never touched before

5. Haptic recognition using hierarchical extreme learning machine with local-receptive-field

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Classification of Visual-Tactile Fusion Object Attributes based on the GAMP Attention Mechanism;2024 IEEE 6th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC);2024-05-24

2. Visual–tactile fusion object classification method based on adaptive feature weighting;International Journal of Advanced Robotic Systems;2023-07-01

3. Visual-Haptic-Kinesthetic Object Recognition with Multimodal Transformer;Artificial Neural Networks and Machine Learning – ICANN 2023;2023

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