Semantic Segmentation of Sorghum Using Hyperspectral Data Identifies Genetic Associations
This study describes the evaluation of a range of approaches to semantic segmentation of hyperspectral images of sorghum plants, classifying each pixel as either nonplant or belonging to one of the three organ types (leaf, stalk, panicle). While many current methods for segmentation focus on separat...
Κύριοι συγγραφείς: | Chenyong Miao, Alejandro Pages, Zheng Xu, Eric Rodene, Jinliang Yang, James C. Schnable |
---|---|
Μορφή: | Άρθρο |
Γλώσσα: | English |
Έκδοση: |
American Association for the Advancement of Science (AAAS)
2020-01-01
|
Σειρά: | Plant Phenomics |
Διαθέσιμο Online: | http://dx.doi.org/10.34133/2020/4216373 |
Παρόμοια τεκμήρια
Παρόμοια τεκμήρια
-
3D reconstruction identifies loci linked to variation in angle of individual sorghum leaves
ανά: Michael C. Tross, κ.ά.
Έκδοση: (2021-12-01) -
A UAV‐based high‐throughput phenotyping approach to assess time‐series nitrogen responses and identify trait‐associated genetic components in maize
ανά: Eric Rodene, κ.ά.
Έκδοση: (2022-01-01) -
Fully‐connected semantic segmentation of hyperspectral and LiDAR data
ανά: Hakan Aytaylan, κ.ά.
Έκδοση: (2019-04-01) -
FUSION OF LIDAR AND HYPERSPECTRAL DATA FOR SEMANTIC SEGMENTATION OF FOREST TREE SPECIES
ανά: E. Tusa, κ.ά.
Έκδοση: (2020-08-01) -
Image Filtering to Improve Maize Tassel Detection Accuracy Using Machine Learning Algorithms
ανά: Eric Rodene, κ.ά.
Έκδοση: (2024-03-01)