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What Is Image Recognition? How Has It Impacted Digital Marketing?

Did you know that we can now search for information on the Internet, using images?

Image recognition with Deep Learning and the result of advances in Artificial Intelligence is already used in many spheres of society.

What is image recognition?
Digital image recognition is used to identify objects of interest within an image and recognize to which category they belong.

It implies that machines learn to detect patterns and segment which category they belong to, through artificial intelligence. To do this, this technology uses a set of technologies and machine learning techniques to create neural networks.

The layers of neurons form a set that communicates to analyze the information of each pixel of an image.

Although it is still a developing technology, applications of virtual image recognition have grown in sectors such as healthcare, retail, security, agriculture, and others.

There are automatic learning models of image recognition that are reaching a high degree of development and social involvement. For example:
- Support Vector Machines

These machines make histograms of images that contain the target objects and also of images that do not contain them. The algorithms will compare the parameters of various parts of the image to check for matches.

- Bag of features models

These models take the image to be scanned and a sample photo of the object to be found to match the features of the sample photo to various parts of the target image to see if any matches are found.

- Viola-Jones algorithm

Perhaps one of the best known, Viola-Jones is a facial recognition algorithm widely used in the days before convolutional neural networks, as it scans faces and extracts features that were compared in a series of classifiers.

To successfully find a match, a test image must generate a positive result from each of these classifiers.

- Image recognition models with Deep Learning

Deep learning has fueled the development of image recognition programs such as YOLO, SSD, and RCNN, which use convolution layers to analyze an image or photograph
Image recognition and optimization of Digital Marketing
Like all technology developed based on Artificial Intelligence, image recognition aims to facilitate and automate certain tasks that would require a large investment of time and resources for humans.

This technology allows identifying people, places, objects, and any other element that is in an image. It analyzes new images comparing them with the information that it has been storing during its training to classify them and even make decisions automatically.

A simple example of the use of this technology in companies is the Google image search engine, where the user can upload any photograph, and it will return similar images found on the network. At a business level, this allows us to identify products or services similar to those of our business.
Image recognition for product identification has come to boost online sales.

Simply photograph an item for artificial intelligence to identify and report the stock situation: the number of items, if they are missing, if they are labeled, packaging status, etc.

As we explained before, it also optimizes the search for products on the Internet, which directly influences the sales conversion rate. Many large corporations already use this technology to discover products and even sell them, through third-party advertisements.