UNet implementation provided by geodl [27].

<div><p>The application of deep learning for semantic segmentation has revolutionized image analysis, particularly in the geospatial and medical fields. UNet, an encoder-decoder architecture, has been suggested to be particularly effective. However, limitations such as small sample sizes...

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Bibliographic Details
Main Author:	Sarah Farhadpour (20390793) (author)
Other Authors:	Aaron E. Maxwell (8840882) (author)
Published:	2025
Subjects:	Plant Biology Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified valley fill faces small sample sizes revolutionized image analysis rectified linear unit mapping agricultural terraces incorporates dilated convolution future work aimed complex geomorphic landscapes modified unet architectures comparing unet configurations improve model performance default bottleneck layer deep learning approaches 500 image chips enhance segmentation performance base unet architecture deep learning semantic segmentation mobilenetv2 architecture decoder architecture xlink "> study investigates skip connections positive attributes mine benches medical fields inserting squeeze generally adequate general framework g ., excitation modules decoder blocks class imbalance based models architectural modifications advanced modules advanced modifications activation function
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UNet implementation provided by geodl [27].

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