Codesota · Models · PACYan et al.1 results · 1 benchmarks
Model card

PAC.

Yan et al.clustering

Probability Aggregation Clustering. Centerless clustering algorithm designed for deep clustering scenarios. From DPAC paper (ECCV 2024).

§ 01 · Benchmarks

Every benchmark PAC has a recorded score for.

#BenchmarkArea · TaskMetricValueRankDateSource
01pendigitsComputer Vision · Optical Character Recognitionaccuracy78.0%#6/82024-07-07source ↗
Rank column shows this model’s position vs all other models scored on the same benchmark + metric (competitors after the slash). #1 in red means current SOTA. Sorted by rank, then newest result.
§ 02 · Strengths by area

Where PAC actually performs.

Computer Vision
1
benchmark
avg rank #6.0
§ 03 · Papers

1 paper with results for PAC.

  1. 2024-07-07· Computer Vision· 1 result

    Deep Online Probability Aggregation Clustering

    Yuxuan Yan, Na Lu, Ruofan Yan
§ 05 · Sources & freshness

Where these numbers come from.

unknown
1
result
1 of 1 rows marked verified.