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A Parameter-efficient Convolutional Approach for Camouflaged Weed Detection in Multispectral Aerial Imagery
We introduce FCBNet, an efficient model designed for camouflaged weed detection. The architecture is based on a fully frozen ConvNeXt backbone, the proposed Feature Correction Block (FCB), which leverages efficient convolutions for feature refinement, and a lightweight decoder. FCBNet is evaluated o
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