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  • Olivia Sacaridis

Computer Vision: AI for Every Industry

Computer Vision is one of the most versatile and commonly used applications of AI in the enterprise today. It is the use of artificial intelligence algorithms to automatically analyze and act on visual data in lieu of the human eye and judgment. Combining computer vision systems and appropriate optical sensors can also allow machines to capture and take action on visual inputs in real time.

Recent advances in neural network algorithms, computing power and data storage have exponentially accelerated the abilities and applications of computer vision in enterprise.

New machine learning algorithms require just 2% of the lines of code that traditional computer programs would need to recognize patterns and classify images. This enormous jump in efficiency is opening unprecedented doors.

Manufacturing: computer vision is being used to assist in predictive maintenance and quality control. Computer vision based monitoring systems can cut inspection times and increase cost efficiency, while also mitigating safety risks by keeping workers away from hazardous zones.

Healthcare: computer vision is being used to detect cancer, monitor the growth of tumors, assist physicians in offering more precise diagnostics and much more.

Agriculture: computer vision can help monitor livestock, and identify the best practices for raising crops with the ability to detect pests and weeds more quickly and effectively.

Finance: AI assisted identity recognition is helping millions of customers verify their identity and access bank accounts remotely.

Sales and Marketing: computer vision is used to make recommendations and forecast future purchases based on the visual data of a consumer's searches.

The applications of computer vision systems are as limitless as your imagination, but you may be wondering: how much data does one need to take advantage of this booming technology?

When building the machine learning models that these computer vision systems are based on, it is necessary to train the model on unstructured data that is representative of what the computer vision system needs to identify. Lack of data scope or quality may seem like an insurmountable challenge in taking advantage of computer vision, but it does not have to be. Augmenting and creating synthetic visual data can solve this problem, creating new possibilities that base entire computer vision systems off of just a few dozen images. For example, Vaital was featured in VentureBeat for making this elusive aim a reality.

Computer vision technology is ripe to take over simple tasks that require little more than the human eye. At Vaital, we specialize in computer vision and process oriented AI development. Our team can bring you 60+ years of technology leadership to help identify the areas in your business that computer vision and other AI processes can create significant ROI and competitive advantage. Come talk to Vaital.

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