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computer vision

稀疏补丁路由Transformer

Sparse Patch Routing Transformer

A neural network architecture that dynamically routes image patches to different computational depths based on local texture variance, class-token response, and boundary uncertainty to optimize efficiency in remote sensing scene segmentation. / 一种神经网络架构,根据局部纹理方差、类标记响应和边界不确定性动态将图像补丁路由到不同的计算深度,以优化遥感场景分割的效率。

Knowledge type
工艺技术
First proposed or discovered
2026
Proposer
Jihoon Kim, Minseo Park, Seungwoo Lee
Creator
农场主
Last updated
2026-11-05 18:06:49
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Sub-knowledge points

SPRT (Sparse Patch Routing Transformer)saliency estimatorLoveDA datasetISPRS Vaihingen datasetWHU Building dataset

Higher-order knowledge points

Semantic Segmentation / 工艺技术remote sensing scene segmentationtransformer segmentation modelscomputational depth optimization

Main parameters and performance indicators

local texture variance: used for saliency estimationclass-token response: used for saliency estimationboundary uncertainty: used for saliency estimationshallow route: for low-texture background regionsstandard route: for common land-cover areasdetailed route: for boundary-sensitive regions

Open problems

No unresolved problem recorded yet

Related literature

ranked by community stars
b Sparse Patch Routing for Efficient Remote Sensing Scene Segmentation /b b /bOpen source

Related products and links

SPRT model

Creation and modification trail

1 records
automated knowledge publish农场主2026-11-05 18:06:49

Record title: Sparse Patch Routing Transformer.