Dunn et al., 2006 - Google Patents
Vision based macadamia yield assessmentDunn et al., 2006
- Document ID
- 3935715687968405588
- Author
- Dunn M
- Billingsley J
- Bell D
- Publication year
- Publication venue
- Sensor Review
External Links
Snippet
Purpose–To describe the prototype macadamia nut yield monitor. Design/methodology/ approach–In this paper, the machine vision‐based yield monitor for macadamia nut plantations is described. A summary of sensor fusion procedures is presented. Additionally …
- 241000208467 Macadamia 0 title abstract description 9
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
- G01C11/02—Picture taking arrangements specially adapted for photogrammetry or photographic surveying, e.g. controlling overlapping of pictures
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S3/00—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113167779B (en) | Mapping field anomalies using digital images and machine learning models | |
| US10534086B2 (en) | Systems and methods for determining crop yields with high resolution geo-referenced sensors | |
| US9983311B2 (en) | Modular systems and methods for determining crop yields with high resolution geo-referenced sensors | |
| CN102215666B (en) | Vegetation growth condition analysis method, recording medium on which program is recorded, and vegetation growth condition analyzer | |
| EP2633460B1 (en) | System and method for calibrating agricultural measurements | |
| US6601341B2 (en) | Process for in-season fertilizer nitrogen application based on predicted yield potential | |
| Blackmer et al. | Using precision farming technologies to improve management of soil and fertiliser nitrogen | |
| US6516271B2 (en) | Method and apparatus for ultra precise GPS-based mapping of seeds or vegetation during planting | |
| US6553312B2 (en) | Method and apparatus for ultra precise GPS-based mapping of seeds or vegetation during planting | |
| US20160169855A1 (en) | In-Soil Data Monitoring System and Method | |
| Soto et al. | The contribution of precision agriculture technologies to farm productivity and the mitigation of greenhouse gas emissions in the EU | |
| US11716985B2 (en) | Method for remediating developmentally delayed plants | |
| Falco et al. | Influence of soil heterogeneity on soybean plant development and crop yield evaluated using time-series of UAV and ground-based geophysical imagery | |
| Valbuena | Integrating airborne laser scanning with data from global navigation satellite systems and optical sensors | |
| Salam et al. | Signals in the soil: subsurface sensing | |
| WO2015193822A1 (en) | Method and device for measuring vegetation cover on farmland | |
| Feng et al. | Cotton yield estimation based on plant height from UAV-based imagery data | |
| Lamb et al. | Ultra low-level airborne (ULLA) sensing of crop canopy reflectance: A case study using a CropCircle™ sensor | |
| Laurin et al. | Early mapping of industrial tomato in Central and Southern Italy with Sentinel 2, aerial and RapidEye additional data | |
| Dunn et al. | Vision based macadamia yield assessment | |
| Buick | Precision agriculture: an integration of information technologies with farming | |
| US20210185882A1 (en) | Use Of Aerial Imagery For Vehicle Path Guidance And Associated Devices, Systems, And Methods | |
| Miller et al. | Sensor-based measurements of NDVI in small grain and corn fields by tractor, drone, and satellite platforms | |
| Skrzypczyński et al. | Localization of Agricultural Robots: Challenges, Solutions, and a New Approach | |
| Maldaner et al. | Spatial–Temporal Analysis to Investigate the Influence of in-Row Plant Spacing on the Sugarcane Yield |