Codesota · Models · AE-FCNResearch1 results · 1 benchmarks
Model card

AE-FCN.

Researchopen-sourceAutoencoder + Fully Connected Network

85% accuracy combining fMRI and sMRI on ABIDE (Rakic et al., 2020).

§ 01 · Benchmarks

Every benchmark AE-FCN has a recorded score for.

#BenchmarkArea · TaskMetricValueRankDateSource
01ABIDE IMedical · Disease Classificationaccuracy85.0%#4/24source ↗
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 AE-FCN actually performs.

Medical
1
benchmark
avg rank #4.0
§ 04 · Related models

Other Research models scored on Codesota.

DenseNet-121 (Chest X-ray)
8M params · 4 results · 2 SOTA
SimpleNet
2 results · 2 SOTA
DGN
1 result · 1 SOTA
DeepASD
1 result · 1 SOTA
DefectDet (ResNet)
1 result · 1 SOTA
PROXI
1 result · 1 SOTA
ASD-SWNet
2 results
ASDFormer
2 results
§ 05 · Sources & freshness

Where these numbers come from.

research-paper
1
result
0 of 1 rows marked verified.