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Visual Recognition

What is Visual Recognition?

     Visual Recognition is a term for computer technologies that can recognize certain people, animals, objects or other targeted subjects through the use of algorithms and machine learning concepts. The term is connected to “computer vision", which is an overarching label for the process of training computers to “see” like humans, and “image processing,” which is a catch-all term for computers doing intensive work on image data. It is done in many different ways, but many of the top techniques involve the use of convolutional neural networks to filter images through a series of artificial neuron layers. The convolutional neural network was specifically set up for image recognition and similar image processing. Through a combination of techniques such as max pooling, stride configuration and padding, convolutional neural filters work on images to help machine learning programs get better at identifying the subject of the picture.

     Image recognition has come a long way, and is now the topic of a lot of controversy and debate in consumer spaces. Social media giant Facebook has begun to use image recognition aggressively, as has tech giant Google in its own digital spaces. There is a lot of discussion about how rapid advances in image recognition will affect privacy and security around the world.


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Vision AI

Google's solution for Visual Recognition.

   Google Vision AI cosists of AutoML Vision and Vision API, and it helps you derive insights from your images in the cloud or at the edge or use pre-trained models to detect emotion, understand text, and more. 

   With AutoML Vision you can automate the training of your own custom machine learning models. Simply upload images and train custom image models with AutoML Vision’s easy-to-use graphical interface; optimize your models for accuracy, latency, and size; and export them to your application in the cloud, or to an array of devices at the edge.

   Google Cloud’s Vision API offers powerful pre-trained machine learning models through REST and RPC APIs. Assign labels to images and quickly classify them into millions of predefined categories. Detect objects and faces, read printed and handwritten text, and build valuable metadata into your image catalog.

With Google Visions AI you can:

    • Detect objects automatically

    • Gain intelligence at the edge

     • Reduce purchase friction

     • Understand text and act on it

     • Detect explicit content

     • Use data labeling service

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