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potato-disease-classification

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fatemafaria142 / Classification-of-Potato-Disease-A-Hybrid-Deep-Learning-Framework

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This research presents a hybrid deep learning framework combining MobileNet V2 with LSTM, GRU, and Bidirectional LSTM for classifying various potato diseases. The study explores the performance of different architectures to determine the optimal configuration for accurate disease categorization.

image-processing lstm gru stochastic-gradient-descent bidirectional-lstm mobilenet-v2 neural-network-architecture potato-disease-classification hybrid-deep-learning agricultural-disease-detection
  • Updated Aug 10, 2024
  • Jupyter Notebook

gopiashokan / Potato-Disease-Classification-using-Deep-Learning

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Developed a deep learning model using TensorFlow and Convolutional Neural Networks to classify disease images of potato plants, including early blight, late blight, and overall plant health in agriculture. Model achieved an impressive accuracy of 97.8%, empowering farmers with precise treatment applications to enhance crop yield and quality.

python machine-learning deep-learning deployment pipeline algorithms agriculture tensorflow model keras project cnn classification image-classification convolutional-neural-network farmers streamlit potato-disease potato-disease-classification agriculture-technology
  • Updated May 22, 2024
  • Jupyter Notebook

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