Huang and colleagues: densely connected convolutional networks

What changed

Introduced DenseNet, connecting each convolutional layer to preceding feature maps to encourage feature reuse and improve gradient propagation.

Scientific scope

Introduced DenseNet, connecting each convolutional layer to preceding feature maps to encourage feature reuse and improve gradient propagation. Scope limitation: The first preprint appeared in 2016; year follows CVPR 2017 publication. Reported efficiency and accuracy are dataset-specific.

Evidence

The retained primary-source abstract, bibliographic record and stated review scope support this provisional assessment. No independent experimental replication by WRS is claimed. The first preprint appeared in 2016; year follows CVPR 2017 publication. Reported efficiency and accuracy are dataset-specific.

Contributors

• The named authors listed in the linked research record · SCIENCE: Complete source byline retained in the research record; human research direction, method development and evaluation. Individual labor shares are not measured.

• Huang and colleagues: densely connected convolutional networks — original paper
• Huang and colleagues: densely connected convolutional networks — official research page

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

Full scientific record · Browse contribution grades · Request a correction