Summary of Multi-region Transfer Learning For Segmentation Of Crop Field Boundaries in Satellite Images with Limited Labels, by Hannah Kerner et al.
Multi-Region Transfer Learning for Segmentation of Crop Field Boundaries in Satellite Images with Limited Labels
by Hannah Kerner, Saketh Sundar, Mathan Satish
First submitted to arxiv on: 29 Mar 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel approach is presented for automatically delineating polygonal boundaries and interiors of individual crop fields in overhead remotely sensed images, a crucial task for various agricultural applications. By framing field boundary delineation as an instance segmentation problem, researchers can leverage computer vision techniques to estimate cultivated area or predict end-of-season yield. However, the practical applicability of previous work is limited by the assumption that large labeled datasets are available, which is not the case for many regions. To address this challenge, a multi-region transfer learning approach is proposed, adapting model weights for the target region without requiring extensive labeling efforts. The approach outperforms existing methods and demonstrates substantial performance boosts for multiple architectures. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Scientists have developed a new way to identify crop fields in pictures taken from high above the ground. This helps farmers figure out how much land they’re using and how well their crops are doing. The problem is that most farmers don’t have maps with lots of information about where each field starts and ends. To solve this, researchers used special computer learning techniques to find patterns in pictures and use them to identify fields without needing lots of labels beforehand. |
Keywords
» Artificial intelligence » Instance segmentation » Transfer learning
