Dense-TNT: Efficient Vehicle Type Classification Neural Network Using Satellite Imagery
Ruikang Luo, Yaofeng Song, Longfei Ye, Rong Su · 2024
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Description
Ruikang Luo, Yaofeng Song, Longfei Ye, and Rong Su build a lean neural network that names vehicle types in satellite images. Their study was published in twenty twenty-four. Knowing what vehicles are on the road helps traffic systems react and ease congestion.
Pure convolutional networks miss wide scene context, and bad weather blurs their reads. The team's design stacks dense connections inside a transformer-in-transformer frame, joining local detail with global structure. Satellite and aerial views supply richer input than roadside cameras. The network aims to stay accurate in the messy settings where simpler models falter. The authors offer it as an efficient tool for smart traffic monitoring from above.
Catalog record
| CREATOR | Ruikang Luo, Yaofeng Song, Longfei Ye, Rong Su |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 39 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |