Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping II
Proceedings Volume 10218 is from: Logo
9-13 April 2017
Anaheim, California, United States
Front Matter: Volume 10218
Proc. SPIE 10218, Front Matter: Volume 10218, 1021801 (6 June 2017); doi: 10.1117/12.2280884
Field-based Phenotyping with Ground-based and Aerial Sensor Platforms
Proc. SPIE 10218, Scaling up high throughput field phenotyping of corn and soy research plots using ground rovers, 1021802 (8 May 2017); doi: 10.1117/12.2262713
Proc. SPIE 10218, Automated phenotyping of permanent crops, 1021803 (16 May 2017); doi: 10.1117/12.2262784
Proc. SPIE 10218, A custom multi-modal sensor suite and data analysis pipeline for aerial field phenotyping, 1021804 (19 May 2017); doi: 10.1117/12.2262858
Proc. SPIE 10218, Hyperspectral imaging to identify salt-tolerant wheat lines , 1021805 (16 May 2017); doi: 10.1117/12.2262388
Control Systems and Artificial Intelligence in Agricultural UAV Applications
Proc. SPIE 10218, Towards collaboration between unmanned aerial and ground vehicles for precision agriculture, 1021806 (8 May 2017); doi: 10.1117/12.2262049
Proc. SPIE 10218, Automatic mission planning algorithms for aerial collection of imaging-specific tasks , 1021807 (16 May 2017); doi: 10.1117/12.2262817
Proc. SPIE 10218, Melon yield prediction using small unmanned aerial vehicles, 1021808 (16 May 2017); doi: 10.1117/12.2262412
Proc. SPIE 10218, Real-time yield estimation based on deep learning, 1021809 (8 May 2017); doi: 10.1117/12.2263097
Practical Issues for Commercialization of UAVs in Agriculture
Proc. SPIE 10218, Use of UAV for support of intensive agricultural management decisions: from science to commercial applications, 102180A (16 May 2017); doi: 10.1117/12.2267725
Proc. SPIE 10218, A case study of comparing radiometrically calibrated reflectance of an image mosaic from unmanned aerial system with that of a single image from manned aircraft over a same area, 102180B (19 May 2017); doi: 10.1117/12.2263506
Proc. SPIE 10218, UAV remote sensing for phenotyping drought tolerance in peanuts, 102180C (16 May 2017); doi: 10.1117/12.2262496
Proc. SPIE 10218, UAS imaging for automated crop lodging detection: a case study over an experimental maize field, 102180E (8 May 2017); doi: 10.1117/12.2262812
Aerial and Ground-based Sensing of Critical Agricultural Phenotypes and Conditions
Proc. SPIE 10218, Vineyard management in virtual reality: autonomous control of a transformable drone, 102180F (16 May 2017); doi: 10.1117/12.2267726
Proc. SPIE 10218, Distinguishing plant population and variety with UAV-derived vegetation indices, 102180G (16 May 2017); doi: 10.1117/12.2262631
Proc. SPIE 10218, A predictive model for turfgrass color and quality evaluation using deep learning and UAV imageries, 102180H (8 May 2017); doi: 10.1117/12.2262042
Proc. SPIE 10218, 3D reconstruction optimization using imagery captured by unmanned aerial vehicles, 102180I (16 May 2017); doi: 10.1117/12.2254852
The Way Forward in UAV-based Sensing for Agricultural Production
Proc. SPIE 10218, Automated geographic registration and radiometric correction for UAV-based mosaics, 102180K (16 May 2017); doi: 10.1117/12.2263512
Proc. SPIE 10218, Swimming in sensors and drowning in data: what is needed for UASs to be effective?, 102180L (16 May 2017); doi: 10.1117/12.2267721
Proc. SPIE 10218, The remote sensing data from your UAV probably isn't scientific, but it should be!, 102180M (8 May 2017); doi: 10.1117/12.2267722
Poster Session
Proc. SPIE 10218, Automated information-analytical system for thunderstorm monitoring and early warning alarms using modern physical sensors and information technologies with elements of artificial intelligence, 102180P (16 May 2017); doi: 10.1117/12.2279848
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