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Green Version.pdf

isprs-archives-XLII-3-W8-1-2019.pdf
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🔗 Source: int-arch-photogramm-remote-sens-spatial-inf-sci.net
📊 Size: 967 KB
👤 Author: heipke
⬇️ Downloads: 153

Summary

This study proposes a deep learning approach for detecting chestnut clusters using Convolutional Neural Networks (CNNs), specifically the Xception architecture, to classify and segment chestnut fruits from digital terrestrial camera images. The goal is to develop an automatic method for chestnut trees cluster identification, enabling production estimation and multi-temporal crop evaluation. The approach aims to mitigate risks associated with chestnut cultivation, such as desertification and land degradation, by establishing an effective management and monitoring process.

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Description

This study proposes a deep learning approach for detecting chestnut clusters using Convolutional Neural Networks (CNNs), specifically the Xception...

Technical Information

  • File Format: PDF
  • File Size: 967 KB
  • Pages: 7
  • Language: EN
  • Author: heipke
  • Total Downloads: 153
  • Last Updated: 1 week ago

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