Image Recognition

What Is Image recognition

Image recognition, in the context of machine vision, is the ability of software to identify objects, places, people, writing and actions in images. Computers can use machine vision technologies in combination with a camera and artificial intelligence software to achieve image recognition.

While human and animal brains recognize objects with ease, computers have difficulty with the task. Software for image recognition requires deep machine learning. Performance is best on convolutional neural net processors as the specific task otherwise requires massive amounts of power for its compute-intensive nature. Image recognition algorithms can function by use of comparative 3D models, appearances from different angles using edge detection or by components. Image recognition algorithms are often trained on millions of pre-labeled pictures with guided computer learning.Image recognition is used to perform a large number of machine-based visual tasks, such as labeling the content of images with meta-tags, performing image content search and guiding autonomous robots, self-driving cars and accident avoidance systems.
Current and future applications of image recognition include smart photo libraries, targeted advertising, the interactivity of media, accessibility for the visually impaired and enhanced research capabilities. GoogleFacebookMicrosoftApple and Pinterest are among the many companies that are investing significant resources and research into image recognition and related applications. Privacy concerns over image recognition and similar technologies are controversial as these companies can pull a large volume of data from user photos uploaded to their social media platforms.

How Image Recognition Works

Interpreting the visual world is one of those things that’s so easy for humans we’re hardly even conscious we’re doing it. When we see something, whether it’s car, or a tree, or our grandma, we don’t (usually) have to consciously study it before we can tell what it is. For a computer, however, identifying a human being at all (as opposed to a dog or a chair or a clock, let alone your grandmother) represents an amazingly difficult problem.
And the stakes for solving that problem are extremely high. Image recognition, and computer vision more broadly, is integral to a number of emerging technologies, from high-profile advances like driverless cars and facial recognition software to more prosaic but no less important developments, like building smart factories that can spot defects and irregularities on the assembly line, or developing software to allow insurance companies to process and categorize photographs of claims automatically.
We’re going to explore the challenge of image recognition and how data scientists are using a special type of neural network to address it.


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