261 - What is global average pooling in deep learning?

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  • Опубликовано: 28 дек 2024

Комментарии • 27

  • @hanemellethy9036
    @hanemellethy9036 2 года назад +2

    I really appreciate your diligence and explanation for each topic in detail. I have learnt many things from your videos and waiting enthusiastically for the new videos every week. Thanks a million.

    • @DigitalSreeni
      @DigitalSreeni  2 года назад +1

      You are very welcome

    • @leisana4097
      @leisana4097 2 года назад

      @@DigitalSreeni Hi, thankyou for explanation. But where can I find the images, it's not in github

  • @channelforstream6196
    @channelforstream6196 2 года назад

    Thanks

    • @DigitalSreeni
      @DigitalSreeni  2 года назад

      Thank you very much for your kind contribution.

  • @Sachinkenny
    @Sachinkenny 2 года назад +1

    Wonderful content 💯

  • @압둘하미드이드리스
    @압둘하미드이드리스 7 дней назад

    Can you explain further, 'global average pooling'?

  • @sinaasadiyan
    @sinaasadiyan 2 года назад

    I really enjoy watching your videos 👌

  • @franciscomassucci
    @franciscomassucci 2 года назад +1

    Thanks a lot for this video. Awesome content. I implemented the global averaging pool and tried to convert the model to ONNX. When I try to read from openCV DNN I get an error due to the GAP. Is there anything in particular I must include in the model to use this with opencv DNN? The error message is related to a squeeze layer automatically created after GAP

  • @mdbayazid6837
    @mdbayazid6837 2 года назад

    Wonderful Sir, Respect. Thanks for explaining every details for the beginners like me. One question: Why do GAP is working as a replacement for flattening

    • @DigitalSreeni
      @DigitalSreeni  2 года назад +1

      Looks like you are asking about the applications of GAP. Stay tuned for the next couple of videos :)

  • @ahmadnurokhim4168
    @ahmadnurokhim4168 2 года назад

    Great video sir, thank you

  • @rs9130
    @rs9130 2 года назад

    thank you again for Keras tutorials,
    can you please make a video on domain adaptation using adversarial training, where we need to add segmentation loss and adv discriminator loss. I tried to implement like your srgan tutorial using the combined model and assigning weights, but the results are not as expected.
    thank you

  • @abdelmoula2
    @abdelmoula2 2 года назад

    Hello Sir, wonderful channel. Can you make an excption and put the next video before next week :) Another point, since we are trying to connect all together, it can be good to make the next video as extension of last week video for Anomaly Detection using the same model we trained last week. Thanks

  • @minhaoling3056
    @minhaoling3056 2 года назад

    Hi Sir, what book or lecture videos will u recommend to master ML and DL for someone coming from biology background?

  • @marceloguatura
    @marceloguatura 2 года назад

    thank you! very nice class!

  • @RafiKhalil
    @RafiKhalil 2 года назад

    Good video but Respected Sir, I am still waiting for Mitosis detection video using Mask R-CNN. Hope this time you will make the video for me.!!

    • @DigitalSreeni
      @DigitalSreeni  2 года назад

      I am not sure if I can make such tutorials in the next couple of months. As you can see, each video is like a mini project that involves data gathering, annotations (if custom data), training, and then coming up with training script. Since I do not have any base mask-RCNN code that I worked with as part of my videos, it takes a lot of effort to create such a video. I am hoping to get into it some day but I do not see it happening in the near future. Thanks for the suggestion though, it helps in prioritizing my work.

    • @RafiKhalil
      @RafiKhalil 2 года назад

      @@DigitalSreeni ok sir, no problem, hope in near future you will make a video on Mask R-CNN.

  • @helamahersia
    @helamahersia 2 года назад

    Very useful, thanks a lot :)

  • @ameerazam3269
    @ameerazam3269 2 года назад

    thank you Again

  • @mehdismaeili3743
    @mehdismaeili3743 2 года назад

    hi thanks for this video.

  • @piotr780
    @piotr780 Год назад

    LOL 15 minutes for concept such easy like this 😂