I am trying to build a classification algorithm having 28 classes. These classes consists of Logo of companies like adidas , Nike etc. I have very low dataset below than 100 images and greater than 70 images. I have trained CNN model but not got decent results . Accuracy is not good. I want to switch on pretrained model. I don't know which pretrained model should I use either VGG , ResNet etc. because I saw on Internet that you may use Pretrained model on similar dataset but I have logo of companies , I don't know that any pre trained model is trained on such similar type of objects or not. How should I choose pre trained model that will performs well on my dataset.

  • 1
    $\begingroup$ We can't really know - as is typical with these type of things, you probably just have to give it a try and see for yourself. $\endgroup$
    – Juho
    Jan 16, 2021 at 19:40
  • $\begingroup$ @Juho Any Guess ? $\endgroup$
    – Hamza
    Jan 16, 2021 at 19:59
  • $\begingroup$ No way to know without trying it. $\endgroup$
    – D.W.
    Jan 16, 2021 at 20:29

1 Answer 1


There's no general answer. In this field, you'll just have to try multiple approaches and see how well they work. We usually won't know what will work best until we try it.

I can suggest three candidate approaches:

  1. Get more data.

  2. Use a pre-trained model and fine-tune it. You can use any state-of-the-art model, pick a version that was pre-trained on ImageNet, and then fine-tune it (either fixing the first n-1 layers and training only the last layer; or training all layers, but with a smaller step size).

  3. Use few-shot learning. This will probably require more sophisticated methods and more study.

Aggressive data augmentation might be useful.

  • $\begingroup$ When I increase the number of Convolutional layers , accuracy goes upward with 2 percent. I have increased up to 4 Hidden layers and got an accuracy of 45% max . What is your perception , should I increase more ? $\endgroup$
    – Hamza
    Jan 17, 2021 at 9:21
  • $\begingroup$ @Hamza, sorry, this site isn't a good fit for what you seem to be looking for. The site is not built for interactive back-and-forth interactions. $\endgroup$
    – D.W.
    Jan 17, 2021 at 19:05

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