AI-Driven Background Segmentation for High-Throughput 3D Plant Scans
Accurate background segmentation in 3D plant phenotyping is crucial for reliable trait assessment but remains challenging. Current methods are either excessively complex, developed for a different domain, or lead to data loss (coordinate-based). This paper addresses these issues by introducing an AI...
Saved in:
| Main Authors: | Serkan Kartal, Jan Masner, Jana Kholova, Alexander Galba, Tharanya Murugesan, Rekha Baddam, Vojtech Mikes, Eva Kanska |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11105418/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
PROBLEMS OF SUBTRACTION OF THE BACKGROUND IN THE PROCESS OF THE INDIVIDUAL RADIATION CONTROL AND RADIATING CONTROL ON OPEN AIR
by: A. I. Grigorev, et al.
Published: (2015-09-01) -
TO A QUESTION OF BACKGROUND SUBTRACTION AT AN INDIVIDUAL RADIATION CONTROL
by: A. I. Grigorev
Published: (2015-08-01) -
Research on the Image Background Base Algorithm Based on the Factor Space Theory
by: Pengxue Zhang, et al.
Published: (2023-08-01) -
Radioactive Background of Granito Madeira, North Amazonas, Brazil
by: Vanderlei Vilaça MOURA, et al.
Published: (2019-02-01) -
Ultraviolet Background Radiation from Not-So-Dark Matter in the Galactic Halo
by: Richard Conn Henry, et al.
Published: (2025-05-01)