Proceedings :: International Society of Precision Agriculture

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Mohammad, A.S

Bresilla, K

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Authors

Nayse, S.P

Mohammad, A.S

Bresilla, K

Manfrini, L

Boini, A

Perulli, G

Morandi, B

Grappadelli, L.C

Topics

Sensor Application in Managing In-season CropVariability

Big Data, Data Mining and Deep Learning

Type

Poster

Oral

Year

2014

2018

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Filter results2 paper(s) found.
1. Application based Wireless Sensor Node for Underground Moisture Sensing for Precision Agriculture In this paper, we are attempting to examine the WUWSN (wireless underground water sensor node*) for precision agriculture. The development and function of this sensor along with its software application is described in this paper. The equipment is under testing and the laboratory results and interpretations are discussed in this paper. This equipment is based on the new concept of sensing underground soil moisture. The sensor is cost effective sensor and has a long... S.P. Nayse, A.S. Mohammad Download paper
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 Download paper

Filter results2 paper(s) found.

1. Application based Wireless Sensor Node for Underground Moisture Sensing for Precision Agriculture

In this paper, we are attempting to examine the WUWSN (wireless underground water sensor node*) for precision agriculture. The development and function of this sensor along with its software application is described in this paper. The equipment is under testing and the laboratory results and interpretations are discussed in this paper. This equipment is based on the new concept of sensing underground soil moisture. The sensor is cost effective sensor and has a long... S.P. Nayse, A.S. Mohammad

Download paper

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

Download paper