Efficient compression of encoder-decoder models for semantic segmentation using the separation index
Abstract We present a novel approach to compressing encoder–decoder architectures, particularly in semantic segmentation tasks, by leveraging the Separation Index (SI)—a metric that quantifies how distinctly a network’s feature maps separate different classes at the pixel level. By identifying and p...
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| Main Authors: | Movahed Jamshidi, Ahmad Kalhor, Abdol-Hossein Vahabie |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-10348-9 |
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