Evaluation of cameras and image distance for CNN-based weed detection in wild blueberry

Patrick J. Hennessy; Travis J. Esau; Arnold W. Schumann; Qamar U. Zaman; Kenneth W. Corscadden; Aitazaz A. Farooque

doi:10.1016/j.atech.2021.100030

Evaluation of cameras and image distance for CNN-based weed detection in wild blueberry

Patrick J. Hennessy, Travis J. Esau, Arnold W. Schumann, Qamar U. Zaman, Kenneth W. Corscadden, Aitazaz A. Farooque

Research output: Contribution to journal › Article › peer-review

Original language	English
Article number	100030
Journal	Smart Agricultural Technology
Volume	2
DOIs	https://doi.org/10.1016/j.atech.2021.100030
Publication status	Published - Dec 2022

ASJC Scopus Subject Areas

General Agricultural and Biological Sciences
Artificial Intelligence
Computer Science (miscellaneous)

Access to Document

10.1016/j.atech.2021.100030

Cite this

@article{9385f2fc6dc04d3e97d7a8b8ae9f4bab,

title = "Evaluation of cameras and image distance for CNN-based weed detection in wild blueberry",

author = "Hennessy, {Patrick J.} and Esau, {Travis J.} and Schumann, {Arnold W.} and Zaman, {Qamar U.} and Corscadden, {Kenneth W.} and Farooque, {Aitazaz A.}",

note = "Funding Information: Funding for this research was generously provided by the Natural Sciences and Engineering Research Council of Canada Discovery Grants Program (RGPIN-06295-2019), Doug Bragg Enterprises, Ltd, and New Brunswick Canadian Agricultural Partnership (CAP). The authors would like to thank Dr. Scott White for helping with field selection for development of the image dataset and the wild blueberry growers in Nova Scotia for use of their fields during image collection. Also, the authors would like to acknowledge the efforts of the mechanized systems and precision agriculture research teams at Dalhousie's Faculty of Agriculture. Publisher Copyright: {\textcopyright} 2021 The Authors",

year = "2022",

month = dec,

doi = "10.1016/j.atech.2021.100030",

language = "English",

volume = "2",

journal = "Smart Agricultural Technology",

issn = "2772-3755",

}

TY - JOUR

T1 - Evaluation of cameras and image distance for CNN-based weed detection in wild blueberry

AU - Hennessy, Patrick J.

AU - Esau, Travis J.

AU - Schumann, Arnold W.

AU - Zaman, Qamar U.

AU - Corscadden, Kenneth W.

AU - Farooque, Aitazaz A.

N1 - Funding Information: Funding for this research was generously provided by the Natural Sciences and Engineering Research Council of Canada Discovery Grants Program (RGPIN-06295-2019), Doug Bragg Enterprises, Ltd, and New Brunswick Canadian Agricultural Partnership (CAP). The authors would like to thank Dr. Scott White for helping with field selection for development of the image dataset and the wild blueberry growers in Nova Scotia for use of their fields during image collection. Also, the authors would like to acknowledge the efforts of the mechanized systems and precision agriculture research teams at Dalhousie's Faculty of Agriculture. Publisher Copyright: © 2021 The Authors

PY - 2022/12

Y1 - 2022/12

UR - http://www.scopus.com/inward/record.url?scp=85127080843&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85127080843&partnerID=8YFLogxK

U2 - 10.1016/j.atech.2021.100030

DO - 10.1016/j.atech.2021.100030

M3 - Article

AN - SCOPUS:85127080843

SN - 2772-3755

VL - 2

JO - Smart Agricultural Technology

JF - Smart Agricultural Technology

M1 - 100030

ER -

Evaluation of cameras and image distance for CNN-based weed detection in wild blueberry

ASJC Scopus Subject Areas

Access to Document

Other files and links

Fingerprint

Dalhousie University Researchers Advance Knowledge in Smart Technology (Evaluation of cameras and image distance for CNN-based weed detection in wild blueberry)

Cite this

Evaluation of cameras and image distance for CNN-based weed detection in wild blueberry

ASJC Scopus Subject Areas

Access to Document

Other files and links

Fingerprint

Press/Media

Dalhousie University Researchers Advance Knowledge in Smart Technology (Evaluation of cameras and image distance for CNN-based weed detection in wild blueberry)

Cite this