A tree crown segmentation model using a trainable Log-Gabor convolutional layer, mixed pooling, and averaged dilated convolutions reports mIoU gains over ResUNet and other baselines on three aerial datasets.
The validation of the mixedwood growth model (mgm) for use in forest management decision making,
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Bridging Classical and Modern Computer Vision: PerceptiveNet for Tree Crown Semantic Segmentation
A tree crown segmentation model using a trainable Log-Gabor convolutional layer, mixed pooling, and averaged dilated convolutions reports mIoU gains over ResUNet and other baselines on three aerial datasets.