“A Novel Software for Fruit Price Prediction Using Machine Learning”
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-6568-7_53
Reference7 articles.
1. Femling F, Olsson A, Alonso-Fernandez F (2018) Fruit and vegetable identification using machine learning for retail applications. In: 2018 14th international conference on signal-image technology and internet-based systems (SITIS), Las Palmas de Gran Canaria, Spain, 2018, pp 9–15. https://doi.org/10.1109/SITIS.2018.00013
2. Hossain MS, Al-Hammadi M, Muhammad G (2019) Automatic fruit classification using deep learning for industrial applications. IEEE Trans Industr Inf 15(2):1027–1034. https://doi.org/10.1109/TII.2018.2875149
3. Fang Y, Min X, Zheng L, Zhang D (2019) Fruit market trend forecast using k means-based deep learning models. In: 2019 IEEE 10th international conference on software engineering and service science (ICSESS), Beijing, China, pp 628–633. https://doi.org/10.1109/ICSESS47205.2019.9040838
4. Apolo-Apolo OE et al (2020) Deep learning techniques for estimation of the yield and size of citrus fruits using a UAV. Eur J Agron 115:126030. https://doi.org/10.1016/j.eja.2020.126030
5. Gill HS, Khehra BS (2022) Fruit image classification using deep learning, 07 November 2022, PREPRINT (Version 1) available at Research Square https://doi.org/10.21203/rs.3.rs-574901/v1
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