Confusion Matrixes for CNN model.

<div><p>Wood species recognition has recently emerged as a vital field in the realm of forestry and ecological conservation. Early studies in this domain have offered various methods for classifying distinct wood species found worldwide using data collected from a particular region. An i...

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Bibliographic Details
Main Author:	Ashrafun Zannat (21807747) (author)
Other Authors:	Md. Saiful Islam (7347884) (author), Md. Shahriar Zaman (21807750) (author), Sadman Saif (21807753) (author)
Published:	2025
Subjects:	Genetics Ecology Science Policy Plant Biology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified stage deep learning several deep learning research practically applicable offered various methods model &# 8217 customized bdwood model bdwood model achieves 85 %, demonstrating wood species classification wood species classification decisions 94 %, 93 %, vital field training accuracy trained models tangible outcome recently emerged providing insights produced results particular region outstanding roc highest accuracy features contributing ensemble technique ecological conservation early studies desired outcome clear winner cam explainability bangladeshi forests bangladeshi forest android application 7119 high 09 %.
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Confusion Matrixes for CNN model.

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