Learning a deeply supervised multi-modal RGB-D embedding for semantic scene and object category recognition-Reference-Cited by-同舟云学术

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Learning a deeply supervised multi-modal RGB-D embedding for semantic scene and object category recognition

Published:2017-06 Issue: Volume:92 Page:41-52
ISSN:0921-8890
Container-title:Robotics and Autonomous Systems
language:en
Short-container-title:Robotics and Autonomous Systems

Author:

Zaki Hasan F.M.^ORCID,Shafait Faisal,Mian Ajmal

Funder

The Ministry of Education Malaysia

International Islamic University of Malaysia

ARC Discovery

Publisher

Elsevier BV

Subject

Computer Science Applications,General Mathematics,Software,Control and Systems Engineering

Reference59 articles.

1. Sliding shapes for 3D object detection in depth images;Song,2014

2. Deep learning for detecting robotic grasps;Lenz;Int. J. Robot. Res.,2015

3. Unsupervised feature learning for 3d scene labeling;Lai,2014

4. HOPC: Histogram of oriented principal components of 3D pointclouds for action recognition;Rahmani,2014

5. Sun RGB-D: A RGB-D scene understanding benchmark suite;Song,2015

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2. MMSNet: Multi-modal scene recognition using multi-scale encoded features;Image and Vision Computing;2022-06

3. When CNNs meet random RNNs: Towards multi-level analysis for RGB-D object and scene recognition;Computer Vision and Image Understanding;2022-03

4. A Recognition Method for Multi-object Information Based on Multi-source Data Fusion;2021 6th International Conference on Robotics and Automation Engineering (ICRAE);2021-11-19

5. Private and common feature learning with adversarial network for RGBD object classification;Neurocomputing;2021-01

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