Summary of Ecocropsaid: Economic Crops Aerial Image Dataset For Land Use Classification, by Sangdaow Noppitak et al.
EcoCropsAID: Economic Crops Aerial Image Dataset for Land Use Classification
by Sangdaow Noppitak, Emmanuel Okafor, Olarik Surinta
First submitted to arxiv on: 5 Nov 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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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 The EcoCropsAID dataset is a comprehensive collection of 5,400 aerial images captured between 2014 and 2018 using Google Earth. The dataset focuses on five key economic crops in Thailand: rice, sugarcane, cassava, rubber, and longan. The images were collected at various crop growth stages, resulting in significant variability within each category and similarities across different categories. This presents substantial challenges for land use classification. The dataset is an interdisciplinary resource that spans remote sensing, geoinformatics, artificial intelligence, and computer vision. Researchers can explore novel approaches using the dataset, such as extracting spatial and temporal features, developing deep learning architectures, and implementing transformer-based models. The study investigates the use of deep learning algorithms to classify economic crop areas in northeastern Thailand, utilizing satellite imagery. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The EcoCropsAID dataset is a big collection of aerial pictures taken from space between 2014 and 2018. These pictures are of five important crops grown in Thailand: rice, sugarcane, cassava, rubber, and longan. The pictures were taken at different times when the crops were growing or harvesting. This makes it hard to tell what’s what because there’s so much variation within each group and similarities between groups. The dataset is special because it combines many areas of research like remote sensing, geoinformatics, artificial intelligence, and computer vision. It could help people find new ways to solve problems in these fields. |
Keywords
» Artificial intelligence » Classification » Deep learning » Transformer
