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In the effects of estimating forest aboveground biomass utilizing 9 sorts of details independently, the CNN-LSTM model reached the top leads to 8 sorts of information, plus the accuracies were being all better than People of the RF model along with the CNN design. Consequently, the potential of CNN-LSTM in estimating aboveground biomass may be very terrific and warrants abide by-up study.
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The role with the pooling layer will be to subsample the characteristic maps produced with the convolutional layer due to Mastering. The convolutional layer, activation layer and pooling layer can be seen since the attribute Understanding/element extraction layer of your CNN, even though the entirely connected layer is the final application from the uncovered features (characteristic map) into the product job.
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