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Squeeze-and-Excitation channel recalibration

Contribution grade

Convolutional visual recognition · Human-designed research method or resource

Reference score150,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Added global spatial pooling and a bottleneck gating network to adaptively rescale convolutional feature channels, enabling SE-enhanced recognition architectures.

Scientific scope

Added global spatial pooling and a bottleneck gating network to adaptively rescale convolutional feature channels, enabling SE-enhanced recognition architectures. Inherits pooling and gating/attention precedents. Nonexclusive sigmoid gates are not normalized Transformer attention. Small FLOP overhead does not imply equal wall-clock overhead; original timings explicitly differ across devices/training implementations. Competition entry results concern an ensemble/configuration, not every SE block.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Inherits pooling and gating/attention precedents. Nonexclusive sigmoid gates are not normalized Transformer attention. Small FLOP overhead does not imply equal wall-clock overhead; original timings explicitly differ across devices/training implementations. Competition entry results concern an ensemble/configuration, not every SE block.

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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