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Information and Communication Technologies for Agriculture—Theme II: Data

Overview of attention for book
Cover of 'Information and Communication Technologies for Agriculture—Theme II: Data'

Table of Contents

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    Book Overview
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    Chapter 1 You Got Data‥‥ Now What: Building the Right Solution for the Problem
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    Chapter 2 Data Fusion and Its Applications in Agriculture
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    Chapter 3 Machine Learning Technology and Its Current Implementation in Agriculture
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    Chapter 4 Application Possibilities of IoT-based Management Systems in Agriculture
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    Chapter 6 Computer Vision-based Detection and Tracking in the Olive Sorting Pipeline
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    Chapter 7 Integrating Spatial with Qualitative Data to Monitor Land Use Intensity: Evidence from Arable Land – Animal Husbandry Systems
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    Chapter 8 Air drill Seeder Distributor Head Evaluation: A Comparison between Laboratory Tests and Computational Fluid Dynamics Simulations
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    Chapter 9 Data-Based Agricultural Business Continuity Management Policies
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    Chapter 10 Soybean Price Trend Forecast Using Deep Learning Techniques Based on Prices and Text Sentiments
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    Chapter 11 Use of Unsupervised Machine Learning for Agricultural Supply Chain Data Labeling
Attention for Chapter 6: Computer Vision-based Detection and Tracking in the Olive Sorting Pipeline
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Citations

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Chapter title
Computer Vision-based Detection and Tracking in the Olive Sorting Pipeline
Chapter number 6
Book title
Information and Communication Technologies for Agriculture—Theme II: Data
Published by
Springer, Cham, January 2022
DOI 10.1007/978-3-030-84148-5_6
Book ISBNs
978-3-03-084147-8, 978-3-03-084148-5
Authors

Georgiou, George, Karvelis, Petros, Gogos, Christos

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 50%
Unknown 1 50%
Readers by discipline Count As %
Agricultural and Biological Sciences 1 50%
Unknown 1 50%

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