Proceedings

Find matching any: Reset
Hansen, N.C
Mukherjee, J
De Waele, T
Add filter to result:
Authors
Sekhon, B.S
Mukherjee, J
Sharma, A
Thind, S.K
Kaur, R
Makkar, M.S
Ahuja, L.R
Saseendran, S.A
Ma, L
Nielsen, D.C
Trout, T.J
Andales, A.A
Hansen, N.C
De Waele, T
Peralta, D
Shahid, A
De Poorter, E
Topics
Remote Sensing Applications in Precision Agriculture
Modelling and Geo-Statistics
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2012
2008
2022
Home » Authors » Results

Authors

Filter results3 paper(s) found.

1. Spectral Models for Estimation of Chlorophyll Content, Nitrogen, Moisture Stress and Growth of Wheat Crop

  Field  experiments  were  conducted  during  2009-10  and  2010-11 at  research  farm  of the department of Farm Machinery and Power Engineering, Punjab Agricultural university, Ludhiana.  Three wheat ... B.S. Sekhon, J. Mukherjee, A. Sharma, S.K. Thind, R. Kaur, M.S. Makkar

2. Use of a Cropping System Model for Soil-specific Optimization of Limited Water

In the arena of modern agriculture, system models capable of simulating the complex interactions of all the relevant processes in the soil-water-plant- atmosphere continuum are widely accepted as potential tools for decision support to optimize crop inputs of water to achieve location specific yield potential while minimizing environmental (soil and water resources) impacts. In a recent study, we calibrated, validated, and applied the CERES-Maize v4.0 model for simulating limited-water irrigation... L.R. Ahuja, S.A. Saseendran, L. Ma, D.C. Nielsen, T.J. Trout, A.A. Andales, N.C. Hansen

3. Supervised Feature Selection and Clustering for Equine Activity Recognition

In this paper we introduce a novel supervised algorithm for equine activity recognition based on accelerometer data. By combining an approach of calculating a wide variety of time-series features with a supervised feature significance test we can obtain the best suited features using just 5 labeled samples per class and without requiring any expert domain knowledge. By using a simple cluster assignment algorithm with these obtained features, we get a classification algorithm that achieves a mean... T. De waele, D. Peralta, A. Shahid, E. De poorter