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For better results in image segmentation, many annotated images are required. The use of U-net can efficiently make use of the annotated images and create better results. Other models used for segmentation are either computationally expensive or fail to fetch the spatial information. The skip connections in the U-net help resolve these issues. The segmentation and localization are done with high accuracy with feasible computations using the U-net model.

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Implementation of 2D U-Net on the GrapesNet Dataset

  • 会议论文

  • 发表日期：

    2025年

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  • Advait A. Dandekar,
  • Anmol J. Patalay,
  • Parul M. Jadhav

摘要

For better results in image segmentation, many annotated images are required. The use of U-net can efficiently make use of the annotated images and create better results. Other models used for segmentation are either computationally expensive or fail to fetch the spatial information. The skip connections in the U-net help resolve these issues. The segmentation and localization are done with high accuracy with feasible computations using the U-net model.