Soil Temperature Prediction via Self-Training: Izmir Case-Reference-Cited by-同舟云学术

Soil Temperature Prediction via Self-Training: Izmir Case

Published:2022-01-20 Issue: Volume: Page:47-62
ISSN:1300-7580
Container-title:Tarım Bilimleri Dergisi
language:
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Author:

TÜYSÜZOĞLU Göksu,BİRANT Derya,KIRANOGLU Volkan

Publisher

Ankara University Faculty of Agriculture

Subject

Plant Science,Agronomy and Crop Science,Animal Science and Zoology

Reference14 articles.

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2. Anton C A, Matei O & Avram A (2019). Collaborative data mining in agriculture for prediction of soil moisture and temperature. In: Computer Science On-line Conference (CSOC 2019), 24-27 April, Zlin, Czech Republic, pp. 141-151

3. Belkin M, Niyogi P & Sindhwani V (2006). Manifold regularization: A geometric framework for learning from labeled and unlabeled examples. Journal of Machine Learning Research 7(Nov): 2399-2434

4. Dadashzadeh M, Abbaspour-Gilandeh Y, Mesri-Gundoshmian T, Sabzi S, Hernández-Hernández J L, Hernández-Hernández M & Arribas J I (2020). Weed classification for site-specific weed management using an automated stereo computer-vision machine-learning system in rice fields. Plants 9(5): 559

5. Giraddi S, Desai S & Deshpande A (2020). Deep Learning for Agricultural Plant Disease Detection. In: Proceedings of the 1st International Conference on Data Science, Machine Learning and Applications (ICDSMLA 2019), 21-22 Nov, Pune, India, pp. 864-871

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