Crop disease detection via ensembled-deep-learning paradigm and ABC Coyote pack optimization algorithm (ABC-CPOA)

Crop disease is a significant issue that affects the growth and yield of crops, leading to financial loss for farmers. Identification and treatment of crop diseases have become challenging due to the increase in the variety of diseases and the lack of knowledge among farmers. To address this issue,...

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Veröffentlicht in:	Multimedia tools and applications Jg. 84; H. 1; S. 37 - 62
Hauptverfasser:	Chithambarathanu, M., Jeyakumar, M. K.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.01.2025 Springer Nature B.V
Schlagworte:	Algorithms Artificial neural networks Color Computer Communication Networks Computer Science Convexity Crop diseases Data Structures and Information Theory Deep learning Feature extraction Heuristic methods Image filters Machine learning Medical imaging Multimedia Information Systems Neural networks Optimization algorithms Optimization models Plant diseases Recurrent neural networks Shape Special Purpose and Application-Based Systems Weighting functions O-DNN Crop disease detection RNN Attribute based -Bi LSTM Self-Improved Coyote Optimization Algorithm
ISSN:	1573-7721, 1380-7501, 1573-7721
Online-Zugang:	Volltext
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