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A Comprehensive Review of Convolutional Neural Networks based Disease Detection Strategies in Potato Agriculture. Potato Research : .
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Stock price prediction using the Sand Cat Swarm Optimization and an improved deep Long Short Term Memory network. Borsa Istanbul Review 24: 32.
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Designing a Smart Agri-Crop Framework on Cotton Production using ABO Optimized Vision Transformer Model. Journal of Machine and Computing : 230.
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Hybrid Ensemble Learning With CNN and RNN for Multimodal Cotton Plant Disease Detection. IEEE Access 12: 198028.
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Explainable ResNet50 learning model based on copula entropy for cotton plant disease prediction. Applied Soft Computing 164: 112009.
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Automated lesion detection in cotton leaf visuals using deep learning. PeerJ Computer Science 10: e2369.
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Advanced deep transfer learning techniques for efficient detection of cotton plant diseases. Frontiers in Plant Science 15: .
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Hybrid Approach of Cotton Disease Detection for Enhanced Crop Health and Yield. IEEE Access 12: 132495.
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Advancements in rice disease detection through convolutional neural networks: A comprehensive review. Heliyon 10: e33328.
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Enhancing stock index prediction: A hybrid LSTM-PSO model for improved forecasting accuracy. PLOS ONE 20: e0310296.
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A Hybrid Approach for Stock Market Price Forecasting Using Long Short-Term Memory and Seahorse Optimization Algorithm. Annals of Data Science : .
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Estimating crop evapotranspiration of wheat-maize rotation system using hybrid convolutional bidirectional Long Short-Term Memory network with grey wolf algorithm in Chinese Loess Plateau region. Agricultural Water Management 301: 108924.
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Advancements in maize disease detection: A comprehensive review of convolutional neural networks. Computers in Biology and Medicine 183: 109222.
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A Composite Meta Model for the Identification of Cotton Pathologies Utilizing an IoT-Enabled Framework and Stacked Generalization Learning Methodology. International Research Journal of Multidisciplinary Technovation : 128.
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