So in the current can be division research area.
Things are moving surprisingly fast.
Not a week goes by when you don't see a huge breakthrough from Google Facebook or Microsoft and so many
aspects of division and I honestly did have a lot more slides detailing all those key advancements in
the field.
However I realize these things are changing so fast and by the time this course goes up and you Demmy
in a month or two goes by it's going to be heavily audited.
Instead I'll tell you that the current fare from the division is completely dominated by disbelief and
convolutional neural networks.
If you want to see so if you want to stay current with the latest developments in computer vision you'll
definitely need to get into deep belief and convolutional your own that's thankfully have put some of
the best materials for these topics here.
Definitely check them out.
Cathy intensive flu a neural net framework's and Stanfords to see as 12:58 class is exceptional.
It's a computer vision neural net loss.
Definitely start with this first and when you choose or when you want to actually get more into the
theory of deep cleaning these links are exceptional as well.
So I told you I'd be sharing some startup ideas and I'm coming through on that now.
So here are 12 awesome startup ideas that if you want feel free to actually implement them.
Just remember to give me at least one percent equity in your company.
Just kidding but that would be nice.
So anyway I'll just quickly share with you some of these ideas.
So the first one I was thinking thinking about was for detection for elderly people.
There is a lot of research in this area and I think it would be quite a good product especially in like
nursing homes or even in elderly people who live alone just being able to figure out if they're in trouble
before it even for would be priceless information.
Secondly let's look at using drones or cameras and drones to find lost hikers.
That would be a good application for computer vision.
What about using the sim drones to become people in crowds or even dealing pickpockets or whatever.
Let's look at number four which is using CCTV footage to create some sort of smart surveillance system
so you can detect when children are near Lake a pool or a balcony edge.
That would be very useful for paranoid parents.
And what about using drones again to actually monitor crops.
You can check harvest levels diseases irrigation issues anything like that.
And what about medical imaging is a huge competing visions fear going on there.
And what about identifying swimmers intuition who may have like a drowning person detection would be
pretty cool as well as finding counterfeit money.
Well what about making a cool novelty viral app maybe one that you can take a picture of your chess
or checkers board and it actually gives you the next best move that you should be making against your
opponent.
That would be pretty sneaky.
But also a very cool app.
Secondly what about taking a picture of any product and it actually brings up reviews and the prices
of that item online.
And I've actually seen people try this already taking a picture of food on a plate and actually giving
it a calories of that food and macros I would be quite useful for especially people on a diet of keeping
strict track of their diet and a lot of work is actually being done in analyzing faeces.
But there's always room for more.
So many cool things you can do with faeces and actually should you fish a lot of mouth detection which
is how a lot of these things do this stuff anyway.
And if you want to see a lot more startup ideas or just ideas for start ups check codes to Stanfords
see us to 2:9 machine learning site.
Dave Dave listed a lot of machine learning projects that students do there a lot of them are actually
quite original and quite exciting stuff.
So finally we come to the last slide in discourse at least for now.
And that's basically discussing open C-v in mobile apps or web apps.
And I'll tell you a bit how to create a setting.
So firstly if you're building a web app or mobile app you can do it two ways you can create it as a
restful API.
Can Use.
And since we're using python we can simply embed.
So if we could enter Django a flask bundle and basically what it means is that you can actually send
information or images to API your API retune something back to you.
So the proof of this is that it can be accessed on any mobile device or a PC or a Mac basically anywhere
it has internet connection and a camera to take the picture.
Obviously it's fine.
It's going to work.
But the problem with that though is that it's actually requires an internet connection so that may be
an issue sometimes getting to is that it can be updated remotely since its cloud based.
And we can offload all the powerful processing that needs to be done.
So that's quite cool.
However we will need to pay for that Wisting So that's a downside and you can do video using an API
at least not in any real time sense it's going to be too much bandwidth and too much issues as well
so video is probably a no no.
Using it using API is so if you're doing a mobile app and you want to do a video analysis like maybe
what Maskerade does or snapshot with filters then you definitely need to do native mobile open C.V and
they are up as open see if it does come and take wrappers for iOS and Android and have listed links
here so we can get started on those as well.
So the proof is that you definitely can do a video based realtime can be division apps and there's no
need to pay for cloud storage as well.
Everything is stored natively on the phone however because everything is done being is being processed
on the phone.
You can't really do very heavy processing on the mobile phone.
However there are techniques like offloading to GPS and parallel processing which can definitely speed
up most apps.
However obviously that's very technical and that's what takes a lot of time and it's definitely more
difficult doing open CVN mobile apps than in Python.
Python is definitely easiest and best way to get started into open C-v and mobile opens is not as sophisticated.
It doesn't have as much online communities and tutorials and support.
So you should probably become pretty good with open CVN in on the first before tackling iOS and Android
applications.
So that said for the course at least for now I will obviously add more content as things come up.
However as it is this is to me main course and I really really hope you enjoyed it and got a lot out
of it.
If there's anything you want to add anything to stress on it can be totally.
Anything can be deep linning augmented reality TV reconstruction.
Those are two topics I haven't touched on in discourse and mainly because they are a bit challenging
in open Zeevi to do a really cool real world applications with them.
However if there's a need for it I will definitely teach it in this course.
So thank you.
Thank you a lot for pitching discourse.
And it was a pleasure being you instructor.