dc.description.abstract |
Succulent plant-like aloes have many medical uses. They use as a laxative, to treat joint
pain, skin inflammation, conjunctivitis, hypertension, stress, etc. It keeps releasing
oxygen all night where other plants release carbon dioxide at night. Classification of
succulent plant is a challenging and important topic to solve for their complex shape and
beauty. Deep learning approach has a strong ability to extract high-level features from a
piece of an image. This paper will introduce a new dataset of succulent plant and all data
of the dataset are real data. We apply deep convolutional neural networks (DCNNs) on
our dataset. First of all, we use the open camera for data collection and the camera
resolution is 640×480 in order that the size of our image is same. Then we collect all the
data from different nurseries in Dhaka city. We choose 9 different classes of succulent
plant. Our total image 3421 where training data set is 2612 and the test data set is 809.
We have used three convolutional layers, three max-pooling layer, three dropout layer
and we also have a fully connected layer. We have run 30 epoch in our model and our
result is really good. We achieve 97.40% accuracy using our model which is the best of
all previous. |
en_US |