Proceedings

Find matching any: Reset
K, S
Bresilla, K
Add filter to result:
Authors
T, S
giriyappa, M
Hanumanthappa, D
Dr., N
K, S
Yogananda, S
Kiran, A
Bresilla, K
Manfrini, L
Boini, A
Perulli, G
Morandi, B
Grappadelli, L.C
Topics
Spatial Variability in Crop, Soil and Natural Resources
Big Data, Data Mining and Deep Learning
Type
Oral
Year
2016
2018
Home » Authors » Results

Authors

Filter results2 paper(s) found.

1. Spatial Variability of Soil Nutrients and Site Specific Nutrient Management in Maize

A field study was conducted during kharif 2014 and rabi 2014-15 at Southern Transition Zone of Karnataka under the jurisdiction of University of Agricultural Sciences, GKVK, Bangalore, India to know the spatial variability for available nutrient content in cultivator’s field and effect of site specific nutrient management in maize. The farmer’s fields have been delineated with each grid size of 50 m x 50 m using geospatial technology. Soil samples from 0-15 cm were... S. T, M. Giriyappa, D. Hanumanthappa, N. Dr., S. K, S. Yogananda, A. Kiran

2. Using Deep Learning - Convolutional Naural Networks (CNNS) for Real-Time Fruit Detection in the Tree

Image/video processing for fruit detection in the tree using hard-coded feature extraction algorithms have shown high accuracy on fruit detection during recent years. While accurate, these approaches even with high-end hardware are still computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks architecture based on single-stage detectors. Using deep-learning techniques eliminates the need for hard-code specific features for specific... K. Bresilla, L. Manfrini, A. Boini, G. Perulli, B. Morandi, L.C. Grappadelli