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Holthaus, D
Hyrien, M
Holpp, M
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Authors
Romier, C
Hyrien, M
Lamker, D
Holpp, M
Anken, T
Seatovic, D
Grueninger, R
Hueppi, R
Spiesman, B
Grijalva, I
Holthaus, D
McCornack, B
Topics
Education and Training in Precision Agriculture
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2012
2008
2024
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Filter results3 paper(s) found.

1. A New Approach to Yield Map Creation

    One of the barriers to using yield maps as a data layer in precision agriculture activities is that the maps being generated to day are not very accurate in representing what really happened in field.  Numerous data errors in the way the data is collected, poor calibration habits on the part of operators... C. Romier, M. Hyrien, D. Lamker

2. 3d Object Recognition, Localization and Treatment of Rumex Obtusifolius in Its Natural Environment

Rumex obtusifolius is one of the most highly competitive and persistent sorts of weed in agriculture. An automatic recognition and plant-treatment system is currently under development as an alternative treatment technique. An infrared-laser triangulation sensor and a high-resolution smart camera are used to generate 3D images of the weeds and their natural environment. In a segmentation process, contiguous surface patches are separated from one other. These 3D surface patches... M. Holpp, T. Anken, D. Seatovic, R. Grueninger, R. Hueppi

3. Sampling Bumble Bees and Floral Resources Using Deep Learning and UAV Imagery

Pollinators, essential components of natural and agricultural systems, forage over relatively large spatial scales. This is especially true of large generalist species, like bumble bees. Thus, it can be difficult to estimate the amount and diversity of floral resources available to them. Floral cover and diversity are often estimated over large areas by extrapolation from small scale samples (e.g., a 1-m quadrat) but the accuracy of such estimates can vary depending on the spatial patchiness of... B. Spiesman, I. Grijalva, D. Holthaus, B. Mccornack