Gupta, Shelly. Plant recognition using convolutional neural network. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2022.
Plant recognition using convolutional neural network
Abstract:
There are currently around 375000 known species of
plants in the world. Expert botanists are able to easily classify
and classify them based on either division/phylum, order, class,
species, genus or family. But common people like students and
new people in the field may find it difficult to classify them
appropriately due to lack of experience or exposure to those
plants.
In the proposed solution, we plan on suggesting a system which
would use deep learning models for image processing. This
system can be trained on an ample amount of plant leaves images
and tree images dataset containing pictures of various plant
leaves and trees. Many prominent datasets like Flavia, Swedish
Leaf datasets, etc can be used to train the model. The model will
be built using a combination of 2-D Convolutional layers, Max
Pooling and Dense layers. The system will take the images of the
plant or tree as input and the built model will work on and
predict the output. The output will be the classification of the
plant.
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2022
Modified:
2024-05-14
Issued:
2024-05-14
บทความ/Article
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BibliograpyCitation :
In IEEE Computer Society. 2022 Fifth International Conference on Computational Intelligence and Communication Technologies (CCICT 2022) (pp.164-168). Los Alamitos, CA : IEEE Computer Society