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Grappadelli, L.C
Wan Ismail, W
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Authors
Wan Ismail, W
Abdul Rahman, K
Bresilla, K
Manfrini, L
Boini, A
Perulli, G
Morandi, B
Grappadelli, L.C
Topics
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Big Data, Data Mining and Deep Learning
Type
Oral
Year
2008
2018
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Filter results2 paper(s) found.

1. Development of Real-time Color Analysis for the On- Line Automated Weeding Operations

Weeds compete with the crop for water, light, nutrients and space, and therefore reduce crop yields and also affect the efficient use of machinery. Chemical sprayer is the most popular method to eradicate weeds but has cause hazardous to the environment, crops and workers. A smart sprayer is required to control the usage of chemical weedicides at the optimal level. Thus an on-line automated sprayer is introduced to the Malaysian farmers to locate in the real time environment the existence and... W. Wan ismail, K. Abdul rahman

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