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SegNet: pooling-index-guided decoding for image segmentation

Passed encoder max-pooling locations to the decoder for sparse unpooling, then used trainable convolutions to densify features before pixel classification, studying memory–accuracy tradeoffs.

What is recorded here?

Passed encoder max-pooling locations to the decoder for sparse unpooling, then used trainable convolutions to densify features before pixel classification, studying memory–accuracy tradeoffs.

Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.

Scientific scope

Pooling-index unpooling inherits earlier unsupervised and visualization methods; the contribution is its trained segmentation architecture and evaluation. No learned unpooling does not mean the decoder has no learned weights. Storing indices trades memory against information and accuracy.

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People and systems

Vijay Badrinarayanan; Alex Kendall; Roberto Cipolla

Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.

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English catalogue narrative

SegNet: pooling-index-guided decoding for image segmentation

Passed encoder max-pooling locations to the decoder for sparse unpooling, then used trainable convolutions to densify features before pixel classification, studying memory–accuracy tradeoffs.

Scientific scope

Pooling-index unpooling inherits earlier unsupervised and visualization methods; the contribution is its trained segmentation architecture and evaluation. No learned unpooling does not mean the decoder has no learned weights. Storing indices trades memory against information and accuracy.

Reading status

This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.

People and systems

Vijay Badrinarayanan; Alex Kendall; Roberto Cipolla

Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.

Original sources