A Novel Approach for Agricultural Crop Classification with Incremental Learning
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-2082-8_4
Reference22 articles.
1. Elbasi E et al (Aug 2023) Crop prediction model using machine learning algorithms. Appl Sci (Switzerland) 13(16). https://doi.org/10.3390/app13169288
2. Ommane Y, Mohammed U, Polytechnique VI, Rhanbouri MA, Benjelloun S (2022) Machine learning based recommender systems for crop selection: a systematic literature review. https://doi.org/10.21203/rs.3.rs-1224662/v2
3. Manjunath MC, Palayyan BP (2023) An efficient crop yield prediction framework using hybrid machine learning model. Revue d’Intelligence Artificielle 37(4):1157–1167. https://doi.org/10.18280/ria.370428
4. Talaat FM (2023) Crop yield prediction algorithm (CYPA) in precision agriculture based on IoT techniques and climate changes. Neural Comput Appl 35(23):17281–17292. https://doi.org/10.1007/s00521-023-08619-5
5. Folorunso O et al (01 Jun 2023) Exploring machine learning models for soil nutrient properties prediction: a systematic review. Big Data Cogn Comput 7(2). MDPI. https://doi.org/10.3390/bdcc7020113
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