Self-Supervised Learning for Panoptic Segmentation of Multiple Fruit Flower Species-Reference-Cited by-同舟云学术

Self-Supervised Learning for Panoptic Segmentation of Multiple Fruit Flower Species

Published:2022-10 Issue:4 Volume:7 Page:12387-12394
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Siddique Abubakar¹^ORCID,Tabb Amy²^ORCID,Medeiros Henry³^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, Marquette University, Milwaukee, WI, USA

2. United States Department of Agriculture (USDA), Kearneysville, WV, USA

3. Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, USA

Funder

National Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Link

https://ieeexplore.ieee.org/ielam/7083369/9831196/9928359-aam.pdf

Reference46 articles.

1. Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers

2. EfficientPS: Efficient Panoptic Segmentation

3. Multi-Task Self-Supervised Object Detection via Recycling of Bounding Box Annotations

4. Leveraging Seen and Unseen Semantic Relationships for Generative Zero-Shot Learning

5. Universal domain adaptation through self-supervision;saito;Proc Neural Inf Process Syst,0

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