241 related articles for article (PubMed ID: 29670055)
1. A New Vegetation Segmentation Approach for Cropped Fields Based on Threshold Detection from Hue Histograms.
Hassanein M; Lari Z; El-Sheimy N
Sensors (Basel); 2018 Apr; 18(4):. PubMed ID: 29670055
[TBL] [Abstract][Full Text] [Related]
2. Using Deep Learning and Low-Cost RGB and Thermal Cameras to Detect Pedestrians in Aerial Images Captured by Multirotor UAV.
de Oliveira DC; Wehrmeister MA
Sensors (Basel); 2018 Jul; 18(7):. PubMed ID: 30002290
[TBL] [Abstract][Full Text] [Related]
3. Coupling of machine learning methods to improve estimation of ground coverage from unmanned aerial vehicle (UAV) imagery for high-throughput phenotyping of crops.
Hu P; Chapman SC; Zheng B
Funct Plant Biol; 2021 Jul; 48(8):766-779. PubMed ID: 33663681
[TBL] [Abstract][Full Text] [Related]
4. Applications of Unmanned Aerial Vehicle Based Imagery in Turfgrass Field Trials.
Zhang J; Virk S; Porter W; Kenworthy K; Sullivan D; Schwartz B
Front Plant Sci; 2019; 10():279. PubMed ID: 30930917
[TBL] [Abstract][Full Text] [Related]
5. UAV and Machine Learning Based Refinement of a Satellite-Driven Vegetation Index for Precision Agriculture.
Mazzia V; Comba L; Khaliq A; Chiaberge M; Gay P
Sensors (Basel); 2020 Apr; 20(9):. PubMed ID: 32365636
[TBL] [Abstract][Full Text] [Related]
6. Identification and Comprehensive Evaluation of Resistant Weeds Using Unmanned Aerial Vehicle-Based Multispectral Imagery.
Xia F; Quan L; Lou Z; Sun D; Li H; Lv X
Front Plant Sci; 2022; 13():938604. PubMed ID: 35937335
[TBL] [Abstract][Full Text] [Related]
7. A model for phenotyping crop fractional vegetation cover using imagery from unmanned aerial vehicles.
Wan L; Zhu J; Du X; Zhang J; Han X; Zhou W; Li X; Liu J; Liang F; He Y; Cen H
J Exp Bot; 2021 Jun; 72(13):4691-4707. PubMed ID: 33963382
[TBL] [Abstract][Full Text] [Related]
8. Automatic Hotspot and Sun Glint Detection in UAV Multispectral Images.
Ortega-Terol D; Hernandez-Lopez D; Ballesteros R; Gonzalez-Aguilera D
Sensors (Basel); 2017 Oct; 17(10):. PubMed ID: 29036930
[TBL] [Abstract][Full Text] [Related]
9. Cotton Yield Estimation Based on Vegetation Indices and Texture Features Derived From RGB Image.
Ma Y; Ma L; Zhang Q; Huang C; Yi X; Chen X; Hou T; Lv X; Zhang Z
Front Plant Sci; 2022; 13():925986. PubMed ID: 35783985
[TBL] [Abstract][Full Text] [Related]
10. Application of Multilayer Perceptron with Automatic Relevance Determination on Weed Mapping Using UAV Multispectral Imagery.
Tamouridou AA; Alexandridis TK; Pantazi XE; Lagopodi AL; Kashefi J; Kasampalis D; Kontouris G; Moshou D
Sensors (Basel); 2017 Oct; 17(10):. PubMed ID: 29019957
[TBL] [Abstract][Full Text] [Related]
11. Phenotyping Conservation Agriculture Management Effects on Ground and Aerial Remote Sensing Assessments of Maize Hybrids Performance in Zimbabwe.
Gracia-Romero A; Vergara-Díaz O; Thierfelder C; Cairns JE; Kefauver SC; Araus JL
Remote Sens (Basel); 2018; 10(2):349. PubMed ID: 32704486
[TBL] [Abstract][Full Text] [Related]
12. An Improved Crop Scouting Technique Incorporating Unmanned Aerial Vehicle-Assisted Multispectral Crop Imaging into Conventional Scouting Practice for Gummy Stem Blight in Watermelon.
Kalischuk M; Paret ML; Freeman JH; Raj D; Da Silva S; Eubanks S; Wiggins DJ; Lollar M; Marois JJ; Mellinger HC; Das J
Plant Dis; 2019 Jul; 103(7):1642-1650. PubMed ID: 31082305
[TBL] [Abstract][Full Text] [Related]
13. Integration of remote-weed mapping and an autonomous spraying unmanned aerial vehicle for site-specific weed management.
Hunter JE; Gannon TW; Richardson RJ; Yelverton FH; Leon RG
Pest Manag Sci; 2020 Apr; 76(4):1386-1392. PubMed ID: 31622004
[TBL] [Abstract][Full Text] [Related]
14. A fully convolutional network for weed mapping of unmanned aerial vehicle (UAV) imagery.
Huang H; Deng J; Lan Y; Yang A; Deng X; Zhang L
PLoS One; 2018; 13(4):e0196302. PubMed ID: 29698500
[TBL] [Abstract][Full Text] [Related]
15. Rapeseed Seedling Stand Counting and Seeding Performance Evaluation at Two Early Growth Stages Based on Unmanned Aerial Vehicle Imagery.
Zhao B; Zhang J; Yang C; Zhou G; Ding Y; Shi Y; Zhang D; Xie J; Liao Q
Front Plant Sci; 2018; 9():1362. PubMed ID: 30298081
[TBL] [Abstract][Full Text] [Related]
16. Estimation of Nitrogen Nutrition Status in Winter Wheat From Unmanned Aerial Vehicle Based Multi-Angular Multispectral Imagery.
Lu N; Wang W; Zhang Q; Li D; Yao X; Tian Y; Zhu Y; Cao W; Baret F; Liu S; Cheng T
Front Plant Sci; 2019; 10():1601. PubMed ID: 31921250
[TBL] [Abstract][Full Text] [Related]
17. Ramie Yield Estimation Based on UAV RGB Images.
Fu H; Wang C; Cui G; She W; Zhao L
Sensors (Basel); 2021 Jan; 21(2):. PubMed ID: 33477949
[TBL] [Abstract][Full Text] [Related]
18. Citrus Tree Segmentation from UAV Images Based on Monocular Machine Vision in a Natural Orchard Environment.
Chen Y; Hou C; Tang Y; Zhuang J; Lin J; He Y; Guo Q; Zhong Z; Lei H; Luo S
Sensors (Basel); 2019 Dec; 19(24):. PubMed ID: 31888248
[TBL] [Abstract][Full Text] [Related]
19. Using unmanned aerial systems and deep learning for agriculture mapping in Dubai.
El Hoummaidi L; Larabi A; Alam K
Heliyon; 2021 Oct; 7(10):e08154. PubMed ID: 34703924
[TBL] [Abstract][Full Text] [Related]
20. Detecting Pest-Infested Forest Damage through Multispectral Satellite Imagery and Improved UNet+.
Zhang J; Cong S; Zhang G; Ma Y; Zhang Y; Huang J
Sensors (Basel); 2022 Sep; 22(19):. PubMed ID: 36236538
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]