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Large datasets and parameter tuning are needed for many advanced and lightweight convolutional neural networks. The new lightweight model is based on CNN's scaling-based design. From Sentinel-2 photos, the new model was successfully measuring sequestered carbon in the aboveground forest biomass. We also produced three different types of training data sets. The new training datasets were divided into six qualitative groups. FlexibleNet was superior or comparable to other lightweight or heavy CNN systems in terms of parameter and time requirements, according to the study, according to the number of parameters and time requirements. In addition, FlexibleNet had the highest accuracy compared to these CNN models.
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