Page 243 - SDMD CNKT va CNTT trong tien trinh CNH_HDH DBSCL

TÀI LIỆU THAM KHẢO
Adak, M., & Yumusak, N. (2016). Classification of e-nose aroma data of four fruit
types by ABC-based neural network. Sensors, 16(3), 304.
https://doi.org/10.3390/s16030304
Aghilinategh, N., Dalvand, M. J., & Anvar, A. (2020). Detection of ripeness grades
of berries using an electronic nose. Food Science and Nutrition, 8(9), 4919–
4928. https://doi.org/10.1002/fsn3.1788
Anderson, N. T., Walsh, K. B., Flynn, J. R., & Walsh, J. P. (2021a). Achieving
robustness across season, location and cultivar for a NIRS model for intact
mango fruit dry matter content. II. Local PLS and nonlinear models.
Postharvest Biology and Technology, 171, 111358. https://doi.org/10.1016/j.
postharvbio.2020.111358
Anderson, N. T., Walsh, K. B., Koirala, A., Wang, Z., Amaral, M. H., Dickinson, G.
R., Sinha, P., & Robson, A. J. (2021b). Estimation of fruit load in Australian
mango orchards using machine vision. Agronomy, 11(9), 1711.
https://doi.org/10.3390/agronomy11091711
Anderson, N. T., Walsh, K. B., Subedi, P. P., & Hayes, C. H. (2020). Achieving
robustness across season, location and cultivar for a NIRS model for intact
mango fruit dry matter content. Postharvest Biology and Technology,
168(June), 111202. https://doi.org/10.1016/j.postharvbio.2020.111202
Ayllon, M. A., Cruz, M. J., Mendoza, J. J., & Tomas, M. C. (2019). Detection of
overall fruit maturity of local fruits using convolutional neural networks
nd
Through Image Processing. Proceedings of the 2 International Conference on
Computing and Big Data - ICCBD 2019, 145–148. https://doi.org/10.1145/
3366650.3366681
Baculo, M. J. C., & Marcos, N. (2018). Automatic mango detection using image
processing and HOG-SVM. Proceedings of the 2018 VII International
Conference on Network, Communication and Computing, 211–215.
https://doi.org/10.1145/3301326.3301358
Baietto, M., & Wilson, A. (2015). Electronic-nose applications for fruit
identification, ripeness and quality grading. Sensors, 15(1), 899–931.
https://doi.org/10.3390/s150100899
Beghi, R., Buratti, S., Giovenzana, V., Benedetti, S., & Guidetti, R. (2017).
Electronic nose and visible-near infrared spectroscopy in fruit and vegetable
monitoring. Reviews in Analytical Chemistry, 36(4), 1–24.
https://doi.org/10.1515/revac-2016-0016
Behera, S. K., Sangita, S., Rath, A. K., & Sethy, P. K. (2019). Automatic
classification of mango using statistical feature and SVM. In Advances in
Computer, Communication and Control: Proceedings of ETES 2018 (pp. 469-
475). Springer Singapore. https://doi.org/10.1007/978-981-13-3122-0

229