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Probable-Class Nearest-Neighbor Ranking

PCNN Ranking

1 paper tagged archive 2025-07-28

Introduced by Giang et al. in PCNN: Probable-Class Nearest-Neighbor Explanations Improve Fine-Grained Image Classification Accuracy for AIs and Humans

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

We present a new class of nearest-neighbor explanations (called Probable-Class Nearest Neighbors or PCNN) and show a novel utility of the XAI method: To improve predictions of a frozen, pretrained classifier C. Our method consistently improves fine-grained image classification accuracy on CUB-200, Cars-196, and Dogs-120. Also, a human study finds that showing lay-users our PCNN explanations improves their decision accuracy over showing only the top-1 class examples (as in prior work).

PaperSource

Papers archive 2025-07-28

1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

4 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Explainable Artificial Intelligence (XAI)1
Fine-Grained Image Classification1
Image Classification1
image-classification1

Usage over time archive 2025-07-28

Papers per year tagged with PCNN Ranking: 2023 to 2023, peak 1 1 0 2023: 1 paper 2023
Papers per year the archive tags with this method, by the paper's archive date (1 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Image Models

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