Effect of directional augmentation using supervised machine learning technologies: A case study of strawberry powdery mildew detection-Reference-Cited by-同舟云学术

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Effect of directional augmentation using supervised machine learning technologies: A case study of strawberry powdery mildew detection

Published:2020-06 Issue: Volume:194 Page:49-60
ISSN:1537-5110
Container-title:Biosystems Engineering
language:en
Short-container-title:Biosystems Engineering

Author:

Shin Jaemyung,Chang Young K.,Heung Brandon,Nguyen-Quang Tri,Price Gordon W.,Al-Mallahi Ahmad

Funder

Natural Science and Engineering Research Council of Canada (NSERC) Discovery

Nova Scotia Research and Innovation Graduate Scholarship Program

Dalhousie Entrance/In-course Scholarship Programs

Publisher

Elsevier BV

Subject

Soil Science,Agronomy and Crop Science,Food Science,Control and Systems Engineering

Reference57 articles.

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2. Accuracies achieved in classifying five leading world crop types and their growth stages using optimal earth observing-1 hyperion hyperspectral narrowbands on google earth engine;Aneece;Remote Sensing,2018

3. Fruit disease detection using color, texture analysis and ANN;Awate,2015

4. Deep learning with unsupervised data labeling for weeds detection on uav images;Bah,2018

5. An investigation of the textural characteristics associated with gray level cooccurrence matrix statistical parameters;Baraldi;IEEE Transactions on Geoscience and Remote Sensing,1995

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