External Features-Based Approach to Date Grading and Analysis with Image Processing
Abstract
Doi: 10.28991/ESJ-2022-06-04-03
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References
Altaheri, H., Alsulaiman, M., & Muhammad, G. (2019). Date Fruit Classification for Robotic Harvesting in a Natural Environment Using Deep Learning. IEEE Access, 7, 117115–117133. doi:10.1109/ACCESS.2019.2936536.
Al-Rahbi, S., Manickavasagan, A., Al-Yahyai, R., Khriji, L., & Alahakoon, P. (2013). Detecting surface cracks on dates using color imaging technique. Food Science and Technology Research, 19(5), 795–804. doi:10.3136/fstr.19.795.
Grossi, M., & Riccò, B. (2017). Electrical impedance spectroscopy (EIS) for biological analysis and food characterization: A review. Journal of Sensors and Sensor Systems, 6(2), 303–325. doi:10.5194/jsss-6-303-2017.
Nasiri, A., Taheri-Garavand, A., & Zhang, Y.-D. (2019). Image-based deep learning automated sorting of date fruit. Postharvest Biology and Technology, 153, 133–141. doi:10.1016/j.postharvbio.2019.04.003.
AKodagali, J., & Balaji, S. (2012). Computer Vision and Image Analysis based Techniques for Automatic Characterization of Fruits-A Review. International Journal of Computer Applications, 50(6). doi:10.5120/7773-0856.
Ruiz-Altisent, M., Ruiz-Garcia, L., Moreda, G. P., Lu, R., Hernandez-Sanchez, N., Correa, E. C., Diezma, B., Nicolaï, B., & García-Ramos, J. (2010). Sensors for product characterization and quality of specialty crops-A review. Computers and Electronics in Agriculture, 74(2), 176–194. doi:10.1016/j.compag.2010.07.002.
Marji, K.A. (2018). Fusion Approach for Dates Fruit Classification. International Journal of Computer Applications, 181(2), 17–20.
Haidar, A., Dong, H., & Mavridis, N. (2012, October). Image-based date fruit classification. In 2012 IV International Congress on Ultra-Modern Telecommunications and Control Systems, 357-363, IEEE. doi:10.1109/ICUMT.2012.6459693.
Alzu’bi, R., Anushya, A., Hamed, E., Al Sha’ar, E. A., & Vincy, B. A. (2018). Dates fruits classification using SVM. AIP Conference Proceedings, 1952(1), 020078, AIP Publishing LLC. doi:10.1063/1.5032040.
F.A.O. (2019). Food and Agriculture Organization of the United Nations. Dates Production. Available online: https://www.fao.org/home/en (accessed on May 2022).
Abdulrahman S. Alturki, Muhammed Islam, Mohammed F. Alsharekh, Mohammed S. Almanee, Anwar H. Ibrahim. (2020). Date Fruits Grading and Sorting Classification Algorithm Using Colors and Shape Features. International Journal of Engineering Research and Technology, 13(8), 1917-1920.
Voulodimos, A., Doulamis, N., Doulamis, A., & Protopapadakis, E. (2018). Deep Learning for Computer Vision: A Brief Review. Computational Intelligence and Neuroscience, 1–13. doi:10.1155/2018/7068349.
Behera, S. K., Rath, A. K., Mahapatra, A., & Sethy, P. K. (2020). Identification, classification & grading of fruits using machine learning & computer intelligence: a review. Journal of Ambient Intelligence and Humanized Computing, 1–11. doi:10.1007/s12652-020-01865-8.
Liakos, K. G., Busato, P., Moshou, D., Pearson, S., & Bochtis, D. (2018). Machine learning in agriculture: A review. Sensors, 18(8), 2674. doi:10.3390/s18082674.
Korohou, T., Okinda, C., Li, H., Cao, Y., Nyalala, I., Huo, L., Potcho, M., Li, X., & Ding, Q. (2020). Wheat Grain Yield Estimation Based on Image Morphological Properties and Wheat Biomass. Journal of Sensors, 2020, 11. doi:10.1155/2020/1571936.
Ziafati Bagherzadeh, S. H., & Toosizadeh, S. (2022). Eye Tracking Algorithm Based on Multi Model Kalman Filter. HighTech and Innovation Journal, 3(1), 15–27. doi:10.28991/hij-2022-03-01-02.
Tharwat, A. (2020). Classification assessment methods. Applied Computing and Informatics, 17(1), 168–192. doi:10.1016/j.aci.2018.08.003.
DOI: 10.28991/ESJ-2022-06-04-03
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