An intelligent mangosteen grading system based on an improved convolutional neural network
Author:
Funder
Chuzhou University
Universiti Malaya
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11760-024-03492-8.pdf
Reference33 articles.
1. Ansori, A.N.M., Fadholly, A., Hayaza, S., Susilo, R.J.K., Inayatillah, B., Winarni, D., Husen, S.A.: A review on medicinal properties of mangosteen (Garcinia mangostana L.). Res. J. Pharm. Technol. 13(2), 974–982 (2020). https://doi.org/10.5958/0974-360X.2020.00182.1
2. Palakawong, C., Delaquis, P.: Mangosteen processing: a review. J. Food Process. Preserv. (2018). https://doi.org/10.1111/jfpp.13744
3. Akhter, I., Javeed, M., Jalal, A.: Deep skeleton modeling and hybrid hand-crafted cues over physical exercises. In: 2023 International conference on communication, computing and digital systems (C-CODE), IEEE, pp. 1–6 (2023). https://doi.org/10.1109/C-CODE58145.2023.10139863
4. Soltani Firouz, M., Sardari, H.: Defect detection in fruit and vegetables by using machine vision systems and image processing. Food Eng. Rev. 14(3), 353–379 (2022). https://doi.org/10.1007/s12393-022-09307-1
5. Azmat, U., Jalal, A., Javeed, M.: Multi-sensors fused IoT-based home surveillance via Bag of visual and motion features. In: 2023 international conference on communication, computing and digital systems (C-CODE), IEEE, pp. 1–6 (2023). https://doi.org/10.1109/C-CODE58145.2023.10139889
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