Automate Tasks that Typically Require Human Vision with Computer Vision
Our AI-Driven Computer Vision models are customized to meet the requirements of your business challenges.
With our CV solutions, objects in images and videos can be identified, classified, and appropriately routed for further analysis as needed, minimizing human interaction.
Beyond facial recognition and autonomous vehicles, Image Analysis is becoming mainstream in many business settings. One example is the insurance industry, where images of storm damage can be quickly assessed based on drone video; another is the railroad industry that has railcar inspections taking place in an office, based on images of trains taken at rail speed with the model flagging only the suspect images for review.
What is Computer Vision?
Computer vision, or Image Analysis, is a field of artificial intelligence wherein computers are trained to interpret and understand images and videos. Using digital images from cameras and videos combined with deep learning models, machines can accurately identify and classify objects. Some examples include identifying damages caused by storms, ensuring proper signage on train tracks based on videos from train-mounted cameras, or detecting cancer cells from medical scans.
The possibilities are endless.
NLP Logix recently joined the NVIDIA Metropolis Partner Program to allow for faster Computer Vision testing and implementation
One use of Image Analysis in the Healthcare industry involves analyzing pathology slides to identify cancer cells. This use case, like most AI applications, is not intended to eliminate the need for a specialist review of the slides, but to augment their review. The process can identify the slides that require a closer analysis.
Click here to learn more about the groundbreaking solutions developed by NLP Logix.
Computer Vision and Machine Learning are used to train computers to recognize damage to roofs, carpets, walls, automobiles, and more, processing large amounts of information with limited human interaction.