148 related articles for article (PubMed ID: 35707612)
1. Automatic Detection and Counting of Wheat Spikelet Using Semi-Automatic Labeling and Deep Learning.
Qiu R; He Y; Zhang M
Front Plant Sci; 2022; 13():872555. PubMed ID: 35707612
[TBL] [Abstract][Full Text] [Related]
2. Segmentation and counting of wheat spike grains based on deep learning and textural feature.
Xu X; Geng Q; Gao F; Xiong D; Qiao H; Ma X
Plant Methods; 2023 Aug; 19(1):77. PubMed ID: 37528413
[TBL] [Abstract][Full Text] [Related]
3. SpikeSegNet-a deep learning approach utilizing encoder-decoder network with hourglass for spike segmentation and counting in wheat plant from visual imaging.
Misra T; Arora A; Marwaha S; Chinnusamy V; Rao AR; Jain R; Sahoo RN; Ray M; Kumar S; Raju D; Jha RR; Nigam A; Goel S
Plant Methods; 2020; 16():40. PubMed ID: 32206080
[TBL] [Abstract][Full Text] [Related]
4.
Sadeghi-Tehran P; Virlet N; Ampe EM; Reyns P; Hawkesford MJ
Front Plant Sci; 2019; 10():1176. PubMed ID: 31616456
[TBL] [Abstract][Full Text] [Related]
5. Detection and analysis of wheat spikes using Convolutional Neural Networks.
Hasan MM; Chopin JP; Laga H; Miklavcic SJ
Plant Methods; 2018; 14():100. PubMed ID: 30459822
[TBL] [Abstract][Full Text] [Related]
6. Determination of wheat spike and spikelet architecture and grain traits using X-ray Computed Tomography imaging.
Zhou H; Riche AB; Hawkesford MJ; Whalley WR; Atkinson BS; Sturrock CJ; Mooney SJ
Plant Methods; 2021 Mar; 17(1):26. PubMed ID: 33750418
[TBL] [Abstract][Full Text] [Related]
7. Wheat ear counting in-field conditions: high throughput and low-cost approach using RGB images.
Fernandez-Gallego JA; Kefauver SC; Gutiérrez NA; Nieto-Taladriz MT; Araus JL
Plant Methods; 2018; 14():22. PubMed ID: 29568319
[TBL] [Abstract][Full Text] [Related]
8. Wheat ear counting using K-means clustering segmentation and convolutional neural network.
Xu X; Li H; Yin F; Xi L; Qiao H; Ma Z; Shen S; Jiang B; Ma X
Plant Methods; 2020; 16():106. PubMed ID: 32782453
[TBL] [Abstract][Full Text] [Related]
9. Genetic modification of spikelet arrangement in wheat increases grain number without significantly affecting grain weight.
Wolde GM; Mascher M; Schnurbusch T
Mol Genet Genomics; 2019 Apr; 294(2):457-468. PubMed ID: 30591960
[TBL] [Abstract][Full Text] [Related]
10. A Deep Learning-Based Method for Automatic Assessment of Stomatal Index in Wheat Microscopic Images of Leaf Epidermis.
Zhu C; Hu Y; Mao H; Li S; Li F; Zhao C; Luo L; Liu W; Yuan X
Front Plant Sci; 2021; 12():716784. PubMed ID: 34539710
[TBL] [Abstract][Full Text] [Related]
11. Automatic wheat ear counting using machine learning based on RGB UAV imagery.
Fernandez-Gallego JA; Lootens P; Borra-Serrano I; Derycke V; Haesaert G; Roldán-Ruiz I; Araus JL; Kefauver SC
Plant J; 2020 Aug; 103(4):1603-1613. PubMed ID: 32369641
[TBL] [Abstract][Full Text] [Related]
12. Plant Density Effect on Grain Number and Weight of Two Winter Wheat Cultivars at Different Spikelet and Grain Positions.
Li Y; Cui Z; Ni Y; Zheng M; Yang D; Jin M; Chen J; Wang Z; Yin Y
PLoS One; 2016; 11(5):e0155351. PubMed ID: 27171343
[TBL] [Abstract][Full Text] [Related]
13. Delayed development of basal spikelets in wheat explains their increased floret abortion and rudimentary nature.
Backhaus AE; Griffiths C; Vergara-Cruces A; Simmonds J; Lee R; Morris RJ; Uauy C
J Exp Bot; 2023 Sep; 74(17):5088-5103. PubMed ID: 37338600
[TBL] [Abstract][Full Text] [Related]
14. TasselNetv2: in-field counting of wheat spikes with context-augmented local regression networks.
Xiong H; Cao Z; Lu H; Madec S; Liu L; Shen C
Plant Methods; 2019; 15():150. PubMed ID: 31857821
[TBL] [Abstract][Full Text] [Related]
15. Detection method of wheat spike improved YOLOv5s based on the attention mechanism.
Zang H; Wang Y; Ru L; Zhou M; Chen D; Zhao Q; Zhang J; Li G; Zheng G
Front Plant Sci; 2022; 13():993244. PubMed ID: 36247573
[TBL] [Abstract][Full Text] [Related]
16. High expression of the MADS-box gene VRT2 increases the number of rudimentary basal spikelets in wheat.
Backhaus AE; Lister A; Tomkins M; Adamski NM; Simmonds J; Macaulay I; Morris RJ; Haerty W; Uauy C
Plant Physiol; 2022 Jun; 189(3):1536-1552. PubMed ID: 35377414
[TBL] [Abstract][Full Text] [Related]
17. Branching Shoots and Spikes from Lateral Meristems in Bread Wheat.
Wang Y; Miao F; Yan L
PLoS One; 2016; 11(3):e0151656. PubMed ID: 26986738
[TBL] [Abstract][Full Text] [Related]
18. An Exploration of Deep-Learning Based Phenotypic Analysis to Detect Spike Regions in Field Conditions for UK Bread Wheat.
Alkhudaydi T; Reynolds D; Griffiths S; Zhou J; de la Iglesia B
Plant Phenomics; 2019; 2019():7368761. PubMed ID: 33313535
[TBL] [Abstract][Full Text] [Related]
19. The dynamic relationship between cerebellar Purkinje cell simple spikes and the spikelet number of complex spikes.
Burroughs A; Wise AK; Xiao J; Houghton C; Tang T; Suh CY; Lang EJ; Apps R; Cerminara NL
J Physiol; 2017 Jan; 595(1):283-299. PubMed ID: 27265808
[TBL] [Abstract][Full Text] [Related]
20. SlypNet: Spikelet-based yield prediction of wheat using advanced plant phenotyping and computer vision techniques.
Maji AK; Marwaha S; Kumar S; Arora A; Chinnusamy V; Islam S
Front Plant Sci; 2022; 13():889853. PubMed ID: 35991448
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]