Adaptive feature selection with deep learning MBi-LSTM model based paddy plant leaf disease classification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-16475-7.pdf
Reference22 articles.
1. Alruwaili M, Abd El-Ghany S, Shehab A (2019) An enhanced plant disease classifier model based on deep learning techniques. Int J Adv Technol Eng Explor 9(1):7159–7164
2. Atole RR, Park D (2018) A multiclass deep convolutional neural network classifier for detection of common rice plant anomalies. Int J Adv Comput Sci Appl, 9(1)
3. Azim MA, Islam MK, Rahman MM, Jahan F (2021) An effective feature extraction method for rice leaf disease classification. Telkomnika (Telecommunication Computing Electronics and Control) 19(2):463–470
4. Bari BS, Islam MN, Rashid M, Hasan MJ, Razman MAM, Musa RM, Ab Nasir AF, Majeed APA (2021) A real-time approach of diagnosing rice leaf disease using deep learning-based faster R-CNN framework. PeerJ Comput Sci 7:e432
5. Cervený J, Begall S, Koubek P, Nováková P, Burda H. Directionalpreference may enhance hunting accuracy in
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