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Sridharan, S
Santiago, W.E
Swen, W
Twickler, P
Söderström, M
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Authors
Khot, L.R
Ehsani, R
Albrigo, G
Campoy, J
Wellington, C
Swen, W
Camergo Neto, J
Büscher, P
Twickler, P
Marquering, D
Müller, M
Maack, D
Santiago, W.E
Barreto, A.R
Figueredo, D.G
Tinini, R.C
Mederos, B.T
Leite, N.J
Söderström, M
Stadig, H
Martinsson, J
Stenberg, M
Piikki, K
Piikki, K
Söderström, M
Sridharan, S
Sornapudi, S
Hu, Q
Kumpatla, S
Bier, J
Topics
Precision Horticulture
Precision Dairy and Livestock Management
Precision Crop Protection
Remote Sensing Applications in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2012
2014
2016
2022
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Authors

Filter results6 paper(s) found.

1. Validation of Variable Rate Spray Decision Rules in Intricate Micro-Metrological Conditions

This study evaluated validity of modified spray decision rules formed to operate axial fan airblast sprayer retrofitted for use in citrus production. The sprayer was field tested in a spraying... L.R. Khot, R. Ehsani, G. Albrigo, J. campoy, C. Wellington, W. Swen, J. Camergo neto

2. NIRS Sensor Controlled Total-Mixed-Ration For Nutrient Optimized Feeding Of Dairy Cattle

The exact regulation of dry matter, energy and ingredients in fodder rations provides a large advantage in order to optimize an economical animal nutrition. Feed mixer wagons are used to feed Gras and Maize silage together with other components. It can be used in combination with a transponder system for feed concentrate as well as for feeding of a total mixed ration. The online measurement system based on NIR-spectrometric sensors to measure DM-content and other nutrients should... P. Büscher, P. Twickler, D. Marquering, M. Müller, D. Maack

3. Recognition And Classification Of Weeds In Sugarcane Using The Technique Of The Bag Of Words

The production of sugar and ethanol in Brazil is very prominent economically and the reducing costs and improving the production system being necessary. The management crops operations of sugarcane and the control of weed is one of the processes that cause the greatest increase in production costs; because the competition that exists between cane plants and weed, for water, nutrients and sunlight is big, contribute to the loss of up to 20% of the useful cane. The use of image processing techniques... W.E. Santiago, A.R. Barreto, D.G. Figueredo, R.C. Tinini, B.T. Mederos, N.J. Leite

4. CropSAT - a Public Satellite-based Decision Support System for Variable-rate Nitrogen Fertilization in Scandinavia

CropSAT is a free-to-use web application for satellite-based production of variable-rate application (VRA) files of e.g. nitrogen (N) and fungicides currently available in Sweden and Denmark. Even in areas frequently covered by clouds, vegetation index maps from data derived from low-cost or freely available optical satellites can be used in practice as a cost-efficient tool in time-critical applications such as optimized nitrogen use. During the very cloudy year 2015, or more useable images... M. Söderström, H. Stadig, J. Martinsson, M. Stenberg, K. Piikki

5. The New Digital Soil Map of Sweden -Derived for Free Use in Precision Agriculture

The Digital Soil Map of Sweden (DSMS) was finalized in 2015. The present paper describes the mapping strategy, the estimated uncertainty of the primary map layers and its potential use in precision agriculture. The DSMS is a geodatabase with information on the topsoil of the arable land in Sweden. The spatial resolution is 50 m × 50 m and it covers > 90% of the arable land of the country (~2.5 million ha). Non-agriculture land and areas with organic soil are excluded. Access to a number... K. Piikki, M. Söderström

6. A Generative Adversarial Network-based Method for High Fidelity Synthetic Data Augmentation

Digital Agriculture has led to new phenotyping methods that use artificial intelligence and machine learning solutions on image and video data collected from lab, greenhouse, and field environments. The availability of accurately annotated image and video data remains a bottleneck for developing most machine learning and deep learning models. Typically, deep learning models require thousands of unique samples to accurately learn a given task. However, manual annotation of a large dataset will... S. Sridharan, S. Sornapudi, Q. Hu, S. Kumpatla, J. Bier