The paper's best single-model ImageNet comparison shows accuracy improving from ResNet-34 through ResNet-152 on both top-1 and top-5 validation error; ResNet-152 reaches 19.38% top-1 and 4.49% top-5 error, which the paper states surpasses all prior ensemble results listed in Table 5.

The paper's best single-model ImageNet comparison shows accuracy improving from ResNet-34 through ResNet-152 on both top-1 and top-5 validation error; ResNet-152 reaches 19.38% top-1 and 4.49% top-5 error, which the paper states surpasses all prior ensemble results listed in Table 5. · CiteArk

Measurement results

0/18 assessed

0 supported0 disputed or conflicting18 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
8.43%	—	Not assessed
7.89%	—	Not assessed
24.4%	—	Not assessed
7.1%	—	Not assessed
21.59%	—	Not assessed
5.71%	—	Not assessed
21.99%	—	Not assessed
5.81%	—	Not assessed
21.84%	—	Not assessed
5.71%	—	Not assessed
21.53%	—	Not assessed
5.6%	—	Not assessed

The paper's best single-model ImageNet comparison shows accuracy improving from ResNet-34 through ResNet-152 on both top-1 and top-5 validation error; ResNet-152 reaches 19.38% top-1 and 4.49% top-5 error, which the paper states surpasses all prior ensemble results listed in Table 5.

Reported and observed measurements

Assessments (0)

Runs (0)

Measurement results