Record Detail
Advanced Search
Text
Dynamic CNN Combination for Morocco Aromatic and Medicinal Plant Classification
In few last years, deep learning has itself set up as the new strategy for plant classification. Deep learning has a best performance for object recognition. In this paper, we have focused on the case of Morocco aromatic and medicinal plant (AMP) classification. Leaf is an important organ of plant, it has shown satisfying performances for plant classification and recognition In addition to leaves, we have used an others organs of AMP.ie. leaf veins and branches. We have proposed a new model combining dynamically the CNN classification result using the entropy impurity method. In the experiments, we have used VGG16, ResNet50 and Inception V3 CNN models. We have used Keras with Tensorflow backend to build and compile all neural network models. The experiments present that our model shown the higher classification accuracy.
Availability
No copy data
Detail Information
Series Title |
-
|
---|---|
Call Number |
-
|
Publisher | International Journal of Computing and Digital Systems : Bahrain., 2022 |
Collation |
006
|
Language |
English
|
ISBN/ISSN |
2210-142X
|
Classification |
NONE
|
Content Type |
-
|
Media Type |
-
|
---|---|
Carrier Type |
-
|
Edition |
-
|
Subject(s) | |
Specific Detail Info |
-
|
Statement of Responsibility |
-
|
Other Information
Accreditation |
Scopus Q3
|
---|
Other version/related
No other version available
File Attachment
Information
Web Online Public Access Catalog - Use the search options to find documents quickly