Rice MSC Dataset: link
(Kaggle Link --> link)
The Rice Image Dataset is a collection of 75,000 images of rice grains, each of which is labeled with one of five rice varieties: Arborio, Basmati, Ipsala, Jasmine, and Karacadag
Model: "sequential"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
zero_padding2d (ZeroPadding (None, 226, 226, 3) 0
2D)
conv2d (Conv2D) (None, 224, 224, 32) 896
batch_normalization (BatchN (None, 224, 224, 32) 128
ormalization)
max_pooling2d (MaxPooling2D (None, 112, 112, 32) 0
)
zero_padding2d_1 (ZeroPaddi (None, 114, 114, 32) 0
ng2D)
conv2d_1 (Conv2D) (None, 112, 112, 64) 18496
batch_normalization_1 (Batc (None, 112, 112, 64) 256
hNormalization)
max_pooling2d_1 (MaxPooling (None, 56, 56, 64) 0
2D)
flatten (Flatten) (None, 200704) 0
dense (Dense) (None, 128) 25690240
dropout (Dropout) (None, 128) 0
dense_1 (Dense) (None, 64) 8256
dropout_1 (Dropout) (None, 64) 0
dense_2 (Dense) (None, 32) 2080
dropout_2 (Dropout) (None, 32) 0
dense_3 (Dense) (None, 5) 165
=================================================================
Total params: 25,720,517
Trainable params: 25,720,325
Non-trainable params: 192
_________________________________________________________________
1: KOKLU, M., CINAR, I. and TASPINAR, Y. S. (2021). Classification of rice varieties with deep learning methods. Computers and Electronics in Agriculture, 187, 106285.
DOI: https://doi.org/10.1016/j.compag.2021.106285
2: CINAR, I. and KOKLU, M. (2021). Determination of Effective and Specific Physical Features of Rice Varieties by Computer Vision In Exterior Quality Inspection. Selcuk Journal of Agriculture and Food Sciences, 35(3), 229-243.
DOI: https://doi.org/10.15316/SJAFS.2021.252
3: CINAR, I. and KOKLU, M. (2022). Identification of Rice Varieties Using Machine Learning Algorithms. Journal of Agricultural Sciences, 28 (2), 307-325.
DOI: https://doi.org/10.15832/ankutbd.862482
4: CINAR, I. and KOKLU, M. (2019). Classification of Rice Varieties Using Artificial Intelligence Methods. International Journal of Intelligent Systems and Applications in Engineering, 7(3), 188-194.
DOI: https://doi.org/10.18201/ijisae.2019355381