The ability to detect and classify our surroundings and images comes quite early on to humans. The human sight develops context naturally over time to train to identify objects, how far they are, how to tell things apart, whether they are moving, whether an image appears distorted, etc.
But a computer/machine needs to be trained to identify and analyze images. This training is provided by computer vision. Now, what is computer vision? Computer vision is a part of artificial intelligence that enables computers to interpret, identify, evaluate, and derive actionable information from visual data like digital images, videos, etc.
Computer vision works with tools like cameras, data, and algorithms, to see and understand the images the same way the human brain works with retinas, optic nerves, and visual cortex. With training, computer vision enables detecting and analyzing thousands of images per minute and notices indistinguishable issues. It can quickly surpass human skills.
Computer vision needs to be trained with a lot of data to identify and analyze images/videos properly. The more varying the data set, the better the model is trained. Deep learning and convolutional neural networks (CNN) technologies are used to train the computer vision model.
Computer vision is gradually being adopted by businesses across different industries to make sense of vast amounts of multimedia data being generated daily. With the help of computer vision services and solutions, organizations can optimize operations, reduce human efforts, and retrieve valuable information and insights from their data.
Let us look at some of the industries that use computer vision services:
The most popular use case of computer vision from the automotive industry that comes to mind is the self-driver systems used by Tesla cars. Self-driving cars are a reality today only because of computer vision. Through computer vision, autonomous vehicles can detect and evaluate the objects on the road to make crucial decisions like decreasing speed, applying brakes, etc.
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Computer vision is being used heavily in the retail sector. From self-checkout kiosks to preventing checkout thefts, the eCommerce space has advanced technologically, thanks to computer vision. Search, and advertising also makes use of computer vision. The user can easily take a picture of any object in their surroundings like watches, shoes, bags, etc., and the eCommerce platform would return purchasing options to the user. Product recommendations and ad-targeting also make use of visual recognition through computer vision.
The manufacturing of critical equipment can be helped a great deal by computer vision. Computer vision services can perform automated checks of essential plants and equipment. Computer vision can also automate important but repetitive functions like inspecting the faults in manufactured units and maintaining the tools and machines in good shape. These error-prone tasks can be handed over to computer vision, and humans can focus on more strategic tasks.
Computer vision has a lot of value in the healthcare industry. Computer vision technology facilitates the healthcare personnel in routine diagnostics that are time-consuming for human physicians but do not contribute remarkably to the final diagnosis. For example, an algorithm can now measure blood loss during surgery by simply analyzing the pictures of used surgical sponges.
Pattern recognition capabilities of computer vision can also help in the timely detection of significant illnesses. Medical imaging facilitated by computer vision can also convert 2D scans into interactive 3D models, enabling doctors to understand the patient’s health better. Health monitoring, precise diagnosis, analyzing reports, etc., are some other use cases of computer vision in healthcare.
The sports industry is already big on using computer vision technology. From goal-line technology to ball trajectory tracking to teams’ behaviour analysis, computer vision is helping evaluate players’ performance and analyze game strategies. Self-training feedback, automatic curation of highlights generation for cricket and sports, calculation of multiple team players’ poses and movements, etc., are some other emerging computer vision technologies in the sports sector.
Computer vision is helping companies process and analyze a large amount of digital media being generated daily. Maruti Techlabs is a pioneer in developing computer vision solutions across various industry verticals. We ensure that organizations can make sense of their imagerial data by processing countless digital images and videos and training complex models to meet the company’s analytics needs.
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