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Inception–ResNet: residual integration and activation scaling

Contribution grade

Convolutional architecture integration · Human-designed research method or resource

Reference score125,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Combined Inception modules with residual connections and studied activation scaling to stabilize wide residual hybrids, comparing against streamlined non-residual Inception-v4.

Scientific scope

Combined Inception modules with residual connections and studied activation scaling to stabilize wide residual hybrids, comparing against streamlined non-residual Inception-v4. Newly specified residual integration/scaling delta, not another invention for model size/version alone or credit for inherited ResNet/Inception-v3. Source3.08percent top5is a four-model ensemble, not single-model performance or proof residuals are necessary for all deep learning. Originalv1has three authors, not later expanded versions.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Newly specified residual integration/scaling delta, not another invention for model size/version alone or credit for inherited ResNet/Inception-v3. Source3.08percent top5is a four-model ensemble, not single-model performance or proof residuals are necessary for all deep learning. Originalv1has three authors, not later expanded versions.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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