CIFAR-10 residual-network test error improves monotonically from 8.75% at 20 layers to a best-run 6.43% at 110 layers while parameter count rises from 0.27M to 1.7M; the much larger 1202-layer model reverses this trend at 7.93%. Table 6 also reports Maxout, NIN, DSN, FitNet, and Highway comparison results.

CIFAR-10 residual-network test error improves monotonically from 8.75% at 20 layers to a best-run 6.43% at 110 layers while parameter count rises from 0.27M to 1.7M; the much larger 1202-layer model reverses this trend at 7.93%. Table 6 also reports Maxout, NIN, DSN, FitNet, and Highway comparison results. · CiteArk

Measurement results

0/25 assessed

0 supported0 disputed or conflicting25 not assessed

The complete result group stays with its claim. Assessed rows come first; their judgments do not replace the whole-claim conclusion. Expand a row for conditions, sources, and evidence history.

Each row is a measurement with its reported value, latest available observation, and cumulative evidence state.
Reported	Latest observation	Evidence judgment
9.38%	—	Not assessed
8.81%	—	Not assessed
8.22%	—	Not assessed
2.5 million parameters	—	Not assessed
8.39%	—	Not assessed
2.3 million parameters	—	Not assessed
7.54%	—	Not assessed
7.72%	—	Not assessed
0.16 percentage points	—	Not assessed
1.25 million parameters	—	Not assessed
8.8%	—	Not assessed
0.27 million parameters	—	Not assessed

Reported and observed measurements

Assessments (0)

Runs (0)

Measurement results