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Leite, N.J
Liping, C
Min, C
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Authors
Guangwei, W
Zhijun, M
Liping, C
Weiqiang, F
Jianjun, D
Santiago, W.E
Barreto, A.R
Figueredo, D.G
Tinini, R.C
Mederos, B.T
Leite, N.J
Kantipudi, K
Lai, C
Min, C
Chiang, R.C
Lai, C
Min, C
Chiang, R
Hafferman, A
Morgan, S
Topics
Spatial Variability in Crop, Soil and Natural Resources
Precision Crop Protection
Big Data, Data Mining and Deep Learning
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Type
Poster
Oral
Year
2012
2014
2018
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1. Evaluation of Application Effect of the Laser Land Leveling Technology in Typical Areas of China

The technology of laser land leveling can improve the accuracy of land leveling and it is the important measure of improving irrigation efficiency and facilitating more uniform distribution of irrigation water. The technology is more widely used in China in... W. Guangwei, M. Zhijun, C. Liping, F. Weiqiang, D. Jianjun

2. 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

3. Weed Detection Among Crops by Convolutional Neural Networks with Sliding Windows

One of the primary objectives in the field of precision agriculture is weed detection. Detecting and expunging weeds in the initial stages of crop growth with deep learning technique can minimize the usage of herbicides and maximize the crop yield for the farmers. This paper proposes a sliding window approach for the detection of weed regions using convolutional neural networks. The proposed approach involves two processes: (1) Image extraction and labelling, (2) building and training our neural... K. Kantipudi, C. Lai, C. Min, R.C. Chiang

4. Precision Agriculture Research Infrastructure for Sustainable Farming

Precision agriculture is an emerging area at the intersection of engineering and agriculture, with the goal of intelligently managing crops at a microscale to maximize yield while minimizing necessary resource. Achieving these goals requires sensors and systems with predictive models to constantly monitor crop and environment status. Large datasets from various sensors are critical in developing predictive models which can optimally manage necessary resources. Initial experiments at University... C. Lai, C. Min, R. Chiang, A. Hafferman, S. Morgan