Post by account_disabled on Dec 9, 2023 0:23:31 GMT -6
Generically speaking enabling machines with the ability to analyse images is called Computer Vision which in turn is based on Deep Learning a set of automatic learning techniques and technologies based on artificial neural networks. These neural networks are designed to recognise patterns and the more layers the network has the greater its predictive capability. Hence for image recognition deep neural networks DNNs are used which refers to artificial neural networks with possibly hundreds of layers. The leading architecture used for image recognition and detection tasks is Convolutional Neural Networks CNNs which consist of several layers each perceiving small parts of an image that are collected together to represent the entire image.
The layer below then repeats this process on the new image representation. In this way the system learns about the image composition. Blueberry’s Experience At Blueberry we’ve used Google Vision for custom software projects requiring image recognition capabilities Email Marketing List as it allows us to connect our custom code to Google’s image recognition capabilities. We’ve found that Google’s Vision API provides pre trained machine learning models that are able to assign labels to images and quickly classify them into millions of predefined categories. It allows the detection of objects and faces read printed and handwritten text in addition to building a catalogue of valuable metadata.
Google’s Vision API clusters images with similar features together to form a homogeneous set. When a user then searches for an image the API extracts features from the image and determines which cluster it is most likely a part of. This type of capability is of significant value in the e commerce sector as it allows customers searching for a specific product to compare products in the retailer’s online site with their query image and return a ranked list of visually and semantically similar results.
The layer below then repeats this process on the new image representation. In this way the system learns about the image composition. Blueberry’s Experience At Blueberry we’ve used Google Vision for custom software projects requiring image recognition capabilities Email Marketing List as it allows us to connect our custom code to Google’s image recognition capabilities. We’ve found that Google’s Vision API provides pre trained machine learning models that are able to assign labels to images and quickly classify them into millions of predefined categories. It allows the detection of objects and faces read printed and handwritten text in addition to building a catalogue of valuable metadata.
Google’s Vision API clusters images with similar features together to form a homogeneous set. When a user then searches for an image the API extracts features from the image and determines which cluster it is most likely a part of. This type of capability is of significant value in the e commerce sector as it allows customers searching for a specific product to compare products in the retailer’s online site with their query image and return a ranked list of visually and semantically similar results.