Fully Convolutional Network - Custom Semantic Segmentation p.10

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  • Опубліковано 18 лис 2024

КОМЕНТАРІ • 8

  • @eshuowoshishen8547
    @eshuowoshishen8547 4 роки тому +2

    "Classification models are really boring", hahahah, true!

  • @taylormcclenny1416
    @taylormcclenny1416 5 років тому

    Your content is great, Seth! Thank you!

  • @rs9130
    @rs9130 3 роки тому +1

    can you make video on pytorch implementation

  • @shubhamkashyap2070
    @shubhamkashyap2070 4 роки тому

    How can we see intermediate things using tensorboard?

  • @jamilal-idrus1905
    @jamilal-idrus1905 2 роки тому

    is this unsupervised learning method or supervised learning like U-Net?

  • @tedp9146
    @tedp9146 5 років тому

    Hey, two questions: Do you have to create the ground thruths by hand?
    And is upsampling integrated to pytorch or tensorflow? Because if you have to do it yourself it would take a lot of time to run, right?

    • @seth8141
      @seth8141  5 років тому

      Transpose 2D Convolution layers are used for upsampling. They're just layers you add into the model. Here I used an annotation tool to create ground truths. Typically, you would use an annotated dataset and train the model but the way I set this series up was to let you annotate your own data. It takes a while. I think there are faster tools out there for semantic segmentation.

  • @Xiaoxiaoxiaomao
    @Xiaoxiaoxiaomao 2 роки тому

    👍🏻