Bootstrap analysis of overall accuracy, F1-score, precision, and recall across model configurations for mineBenchDL, terraceDL and vfillDL datasets.

<p>Error bars represent variability from 10 bootstrap test samples, highlighting performance stability differences across configurations.</p>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Sarah Farhadpour (20390793) (author)
مؤلفون آخرون:	Aaron E. Maxwell (8840882) (author)
منشور في:	2025
الموضوعات:	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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