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arXiv Computer Vision By Kesong Zheng, Zhi Song, Peizhou Li, Shuyi Yao, Tong Li, Yonglin Shen, Zhenxing Bian

DWFF-Net: A Multi-Scale Farmland System Habitat Identification Method with Adaptive Dynamic Weight Feature Fusion

Read the original on arXiv Computer Vision →

The paper introduces DWFF‑Net, a Dynamic Weighted Feature Fusion Network designed to improve multi‑scale segmentation for agricultural habitat recognition. It employs a frozen DINOv3 encoder, a data‑level adaptive dynamic weighting strategy, and a decoder with a dynamic weight calculation network and hybrid loss. Experiments on an agricultural habitat dataset show significant gains in mIoU and mF1 over static fusion and several baseline models, especially for tiny features such as scattered trees.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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