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North West turns 5, here's why people are obsessed
Author: Sara M Moniuszko, USA TODAY
Published: 10:53 AM EDT June 12, 2018
Updated: 11:12 AM EDT June 15, 2018

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The first child of Kim Kardashian West and Kanye West turns fiveFriday.

Sowhy at such a young age are people so obsessed with her? We investigate five reasons the youngster is a fan favorite.

Let's face it: thanks to their famous parents, celebrity kids like North — especially the first-borns — are the targets of public attention the second they emerge from the womb.As such, North has no shortage of love from mom's millions of followers and dad's music fans.

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A post shared by Kim Kardashian West (@kimkardashian) on

Another reason people are so obsessed with her? Perhaps the layer of mystery that surrounds her. Like other celeb children, even if her parents try to make North's childhoodas "normal" a childhood as possible, we know it can't bethe same as ours was, which makes it fascinating. We can't help but wonder: what is it like to be little North, who is more successful at five than we'll probably ever be?

Party of 5

A post shared by Kim Kardashian West (@kimkardashian) on

As much as there's a layer of mystery to her daily life, North is no stranger to her mom's Instagram feed. Kim often gives fans just enough of North to leave them wanting more. Sometimes these mother-daughter posts seem to be conveniently scheduledfor moments when the family would like to change the subject, like after Kanye's "slavery was a choice" controversy from May.Her approach is different from that ofother celebrity moms like Adele and Eva Mendes, who often shield their kids frommedia and the spotlight completely. Letting her fans see North on a regular basisgives them a sense of connectedness with the 5-year-old.

2. Instead, what you should be worried about is the similarity of pills. Try to solve that problem first. I have a lot of experience with prescription pill identification and I can tell you it’s an incredibly challenging problem.

3. Spend a lot of time gathering data of your example pills you want to recognize. You’ll need the data.

Reply
Rui June 5, 2018 at 8:10 pm

Thanks for the reply, Adrian.

I followed your series of posts which ended with the “Deep learning in production with Keras, Redis, Flask, and Apache” and Ifound it pretty awesome. It would be a solution if the mobile app used the API to perform the classification, what do you think?

What would you recommend to deal with the similarity of the pills and what does this problem so challenging, in your opinion?

In my dataset, I have only 10 or so pictures per class. Would you do data augmentation beforehand?

Thank you so much for you answers! It’s really important for me to get feedback from an expert.

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Adrian Rosebrock June 7, 2018 at 3:16 pm

You could have the API perform classification but keep in mind that will require the mobile device to upload the image to the API which of course requires an internet connection. That may or may not be possible in some situations. You will need to do your research there.

If you have only 10 images per class I would spend your time building a larger dataset. You should be in the 100-1,000 images/class range before trying to train a CNN on pill images.

Reply
Prince Bhatia June 6, 2018 at 4:21 am

I am performing image classification on a data set made of 6 different classes of 2000 images in each class of watermark detection.

I tried your model but achieved the accuracy not more than 69%. I just found out that there are quite similar images but with different watermarks in each class, will they be causing the problem to achieve high accuracy on running my model on CPU version.?

Is there any other model would you recommend?

How can i achieve high rate of accuracy when and what are the parameters do we need to keep in mind while preparing dataset?

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Adrian Rosebrock June 7, 2018 at 3:12 pm

Exactly which methods you should use and which techniques you should try is highly dependent on your project. Without knowing what those six classes are or what your end goal is it’s extremely challenging to provide guidance. My best general advice in this instance would be to read through Deep Learning for Computer Vision with Python where I discuss my tips, tricks, and best practices when training CNNs on datasets.

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