The RNNs Technique

RNNs are designed to recognize patterns in sequences of data. They are particularly useful for time-series data and applications where context from previous inputs is essential.

• Functionality: In plant disease diagnosis, RNNs can be used alongside CNNs to analyze sequences of images or symptoms over time, providing a more accurate diagnosis by considering the progression of symptoms.

• Advantages: RNNs are effective for sequential data and can capture temporal dynamics. When combined with CNNs, they provide a comprehensive analysis of both spatial and temporal features.

The C-RNN model for observation-centered plant identification