Cropland PAtteRNS: Parallel Dimensional Attention Networks and Attention to Dataset Disparity for Crop Segmentation in Satellite Imagery Time Series Data
Paper recorded by Signals 4 on 2026-09-29 in cs.LG. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-29 on arXiv · recorded by Signals 4 on 2026-09-30
Category: cs.LG · 机器学习 · first seen 2026-09-30
Abstract
The landscape of satellite imagery time series datasets and boundary-pushing architectures for cropland segmentation has never been richer. However, in this gold rush, important truths are being missed on both fronts, as a drive for the most novel concepts or the largest datasets pushes finer details to the side. In this paper, we present our hybrid transformer-convolutional model, Cropland Parall
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Cite this page: Cropland PAtteRNS: Parallel Dimensional Attention Networks and Attention to Dataset Disparity for Crop Segmentation in Satellite Imagery Time Series Data: the #2 most recent of 334 cs.LG papers we have recorded (as of 2026-09-29). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/cropland-patterns-parallel-dimensional-attention-networks-and-attention-to-datas.html
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