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In addition, although image recognition is technically a form of machine learning, the Machine Learning category is focused on tools (such as software, APIs, SDKs, and frameworks), that provide other machine learning capabilities, such as recommendation engines and pattern recognition. Although data science and machine learning platforms frequently provide tools for training computer vision models, they are broadly focused and not solely geared toward image recognition. This type of software should be distinguished from related forms of software.

The type of user would determine the format in which this software is accessed, whether that be via a machine learning library or framework, an API or SDK, or via an end-to-end platform. Image recognition software can be used by data scientists to train image recognition models, as well as developers looking to add image recognition features to other software. These capabilities are typically embedded inside intelligent applications. Some other aspects of image recognition include image restoration, object recognition, and scene reconstruction. With this software, images are taken as an input, and a computer vision algorithm provides an output, such as a label or bounding box. Image recognition software, also known as computer vision, allows applications to understand images or videos.