DATASETS

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ALL PUBLICATION LISTS

Name

Data Types

Default Task

Attribute Types

# Instances

# Attributes

Year

Download

Pistachio Image Dataset

 2 Class

Classification Clustering

Image

2148

Image

2022

Download
3512 downloaded

Citation Request

1: SINGH D, TASPINAR YS, KURSUN R, CINAR I, KOKLU M, OZKAN IA, LEE H-N., (2022). Classification and Analysis of Pistachio Species with Pre-Trained Deep Learning Models, Electronics,11 (7), 981. https://doi.org/10.3390/electronics11070981. (Open Access)

DOI: https://doi.org/10.3390/electronics11070981

2: OZKAN IA., KOKLU M. and SARACOGLU R. (2021). Classification of Pistachio Species Using Improved K-NN Classifier. Progress in Nutrition, Vol. 23, N. 2. https://doi.org/10.23751/pn.v23i2.9686. (Open Access)

DOI: https://doi.org/10.23751/pn.v23i2.9686

Name

Data Types

Default Task

Attribute Types

# Instances

# Attributes

Year

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Acoustic Extinguisher Fire Dataset

 2 Class

Classification Clustering

Integer, Real 

17.442

6

2022

Download
1407 downloaded

Citation Request

1: KOKLU M., TASPINAR Y.S., (2021). Determining the Extinguishing Status of Fuel Flames With Sound Wave by Machine Learning Methods. IEEE Access, 9, pp.86207-86216, Doi: 10.1109/ACCESS.2021.3088612
Link: https://ieeexplore.ieee.org/document/9452168 (Open Access)
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9452168

DOI: https://doi.org/10.1109/ACCESS.2021.3088612

2: TASPINAR Y.S., KOKLU M., ALTIN M., (2021). Classification of Flame Extinction Based on Acoustic Oscillations using Artificial Intelligence Methods. Case Studies in Thermal Engineering, 28, 101561, Doi: 10.1016/j.csite.2021.101561
Link: https://www.sciencedirect.com/science/article/pii/S2214157X21007243 (Open Access)

DOI: https://doi.org/10.1016/j.csite.2021.101561

3: TASPINAR Y.S., KOKLU M., ALTIN M., (2022). Acoustic-Driven Airflow Flame Extinguishing System Design and Analysis of Capabilities of Low Frequency in Different Fuels. Fire Technology, Doi: 10.1007/s10694-021-01208-9
Link: https://link.springer.com/content/pdf/10.1007/s10694-021-01208-9.pdf"

DOI: https://doi.org/10.1007/s10694-021-01208-9

Name

Data Types

Default Task

Attribute Types

# Instances

# Attributes

Year

Download

Grapevine Leaves Image Dataset

 5 Class

Classification 

Image

500

Image

2022

Download
1030 downloaded

Citation Request

KOKLU, M., UNLERSEN, M. F., OZKAN, IA., ASLAN, M. F. and SABANCI, K. (2022). A CNN-SVM study based on selected deep features for grapevine leaves classification. Measurement, 188, 110425.

DOI: https://doi.org/10.1016/j.measurement.2021.110425

Name

Data Types

Default Task

Attribute Types

# Instances

# Attributes

Year

Download

Date Fruit Datasets

 7 Class

Classification Clustering

Integer, Real 

898

34

2021

Download
2659 downloaded

Citation Request

KOKLU, M., KURSUN, R., TASPINAR, Y. S. and CINAR, I. (2021). Classification of Date Fruits into Genetic Varieties Using Image Analysis. Mathematical Problems in Engineering, Vol.2021, Article ID: 4793293.

DOI: https://doi.org/10.1155/2021/4793293

Name

Data Types

Default Task

Attribute Types

# Instances

# Attributes

Year

Download

Pumpkin Seeds Dataset

 2 Class

Classification Clustering

Integer, Real 

2500

12

2021

Download
1201 downloaded

Citation Request

KOKLU, M., SARIGIL, S. and OZBEK, O. (2021). The use of machine learning methods in classification of pumpkin seeds (Cucurbita pepo L.). Genetic Resources and Crop Evolution, 68(7), 2713-2726. doi:

DOI: https://doi.org/10.1007/s10722-021-01226-0

Name

Data Types

Default Task

Attribute Types

# Instances

# Attributes

Year

Download

Pistachio Dataset

 2 Class

Classification Clustering

Integer, Real 

2148

16
28

2021

Download
656 downloaded

Citation Request

OZKAN IA., KOKLU M. and SARACOGLU R. (2021). Classification of Pistachio Species Using Improved K-NN Classifier. Progress in Nutrition, Vol. 23, N. 2. https://doi.org/10.23751/pn.v23i2.9686.

DOI:https://doi.org/10.23751/pn.v23i2.9686

Name

Data Types

Default Task

Attribute Types

# Instances

# Attributes

Year

Download

Rice MSC Dataset

 5 Class

Classification Clustering

Integer, Real 

75.000

106

2021

Download
1085 downloaded

Citation Request

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

Name

Data Types

Default Task

Attribute Types

# Instances

# Attributes

Year

Download

Rice Image Dataset

5 Class

Classification

Image

75.000

Image

2021

Download
1832 downloaded

Citation Request

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

Name

Data Types

Default Task

Attribute Types

# Instances

# Attributes

Year

Download

Dry Bean Dataset

7 Class

Classification Clustering

Integer, Real 

13.611

16

2020

Download
892 downloaded

Citation Request

KOKLU, M. and OZKAN, I.A., (2020), “Multiclass Classification of Dry Beans Using Computer Vision and Machine Learning Techniques.” Computers and Electronics in Agriculture, 174, 105507.

DOI: https://doi.org/10.1016/j.compag.2020.105507

UCI Machine Learning Repository: https://archive.ics.uci.edu/ml/datasets/Dry+Bean+Dataset

Name

Data Types

Default Task

Attribute Types

# Instances

# Attributes

Year

Download

Raisin Dataset

 2 Class

Classification Clustering

Integer, Real 

900

7

2020

Download
700 downloaded

Citation Request

CINAR I., KOKLU M. and TASDEMIR S., (2020), “Classification of Raisin Grains Using Machine Vision and Artificial Intelligence Methods”, Gazi Journal of Engineering Sciences, vol. 6, no. 3, pp. 200-209, December, 2020.

DOI: https://doi.org/10.30855/gmbd.2020.03.03

UCI Machine Learning Repository: https://archive.ics.uci.edu/ml/datasets/Raisin+Dataset

Name

Data Types

Default Task

Attribute Types

# Instances

# Attributes

Year

Download

Rice Dataset Cammeo and Osmancik

 2 Class

Classification Clustering

Integer, Real 

3810

9

2019

Download
1074 downloaded

Citation Request

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

UCI Machine Learning Repository: https://archive.ics.uci.edu/ml/datasets/Rice+%28Cammeo+and+Osmancik%29

Name

Data Types

Default Task

Attribute Types

# Instances

# Attributes

Year

Download

Durum Wheat Dataset

3 Class

Classification Clustering

Image, Video, Real

9000

236

2019

Download
481 downloaded

Citation Request

KAYA, E., & SARITAS, I. (2019). Towards a real-time sorting system: identification of vitreous durum wheat kernels using ANN based on their morphological, colour, wavelet and gaborlet features. Computers and Electronics in Agriculture, 166, 105016.

DOI: https://doi.org/10.1016/j.compag.2019.105016