Deep Learning AI Image Recognition

It seems like everyone these days is implementing some form of image recognition such as google facebook and car companies etc. How exactly does a machine learn what a Siberian cat looks like? That is what we will look at today on the feed.

Now, with the help of artificial intelligence, we are able to do meaningful things with each of those squares and hexagons in order to boost our productivity and make our overall lives much easier today.

How an image recognition works

Machine learning is a subset of artificial intelligence that strives on completing specific tasks by prediction based on input and algorithms. If we go even deeper, we learn about deep learning. AI is a subset of machine learning, which attempts to mimic our own brain’s network of neurons to a machine.

Learn every day we’re getting image recognition more involved in order to help us with our personal daily lives. For example, if you see some strange-looking plant in the living room simply point google as its image and it will tell you what it is.

If your discord friend uploads a photo of their new cat and you want to know what breed it is. Just run a google image reverse search and you will find out what it is. Self-driving vehicles need to know where they can drive, which is a road, where are the lanes, where they can make a turn, what the difference is between a red light green light, etc.

Image recognition is a huge part of deep learning. The basic explanation is that in order for that car to know what a stop sign looks like it must be given an image of a stop sign the machine will read the stop sign. Through a variety of algorithms, it will then study the stop sign and analyze how the image is going to look by going section per section what color is the stop sign, what shape is it what’s written on it and where is it usually seen in a driver’s peripheral vision.

If there are any errors, scientists can simply correct them once the image has been completely red. It could be labeled and categorized but why stop with one image in our perspective we don’t really need to think for half a second about what a stop sign is and what we must do when we see it.

We have seen so many stop signs in our lives it is pretty much embedded in our brains. The machine must read many different stop signs for better accuracy. That way it doesn’t matter whether the stop sign is seen during foggy or rainy conditions, during the night, or during the day. The machine has seen a stop sign many times. It can know it’s a stop sign just by looking at its shape and color alone.

If you upload and backup your photos go check out your photos, if you haven’t sorted anything you will notice that Google has done it for you. There’s a category for places, things, videos, and animations. Google has sorted photos into albums based on where Google thinks they belong.

The photos labeled as food, beaches, trains, buses, and whatever else you may have photographed in the past. This is the work of Google’s image recognition analysis. It has analyzed over a million photos on the internet. It’s not just Google that uses image recognition as well if someone uploads a photo and Facebook recognizes it.

It will automatically tag them. It’s kind of creepy considering it’s a privacy concern but some people may appreciate the convenience anyways because it saves some time no matter how cool or scary it is. Image recognition plays a huge role in society and will continue to be in development many companies are continuing to implement image recognition and other AI technologies.

The more we can automate certain tasks with machines the more productive we can be as a society.