Computer Vision is an intriguing branch of Artificial Intelligence with a lot of practical applications. The main goal of computer vision is to allow computers to comprehend their surroundings through sight and make decisions based on that understanding. A massive wave of billion-dollar computer vision businesses is brewing, and Forbes predicts that the computer vision industry will reach USD 49 billion by 2022.
Here we have listed down the top 7 computer vision trends and predictions for 2022:
There’s no avoiding the fact that industrial firms must constantly consider the safety of their employees. It is especially crucial at the pandemic time when computer vision can help determine whether people are wearing masks or other protective gear. Computer vision can help maintain social distance while also ensuring safety.
One of the most hotly debated aspects of computer vision is edge computing. Edge computing, for those unaware, allows data to be processed and analyzed more quickly at the point of collection. It allows for more real-time analysis, understanding, and calculation. Edge computing can also help detect anomalies and reduce latency, making it a good fit for organizations prone to network outages.
Robots Guided By Their Vision:
Robots use for various business tasks, but vision-guided robots are especially beneficial in the manufacturing industry. Businesses may use robots to help them anticipate rising labor costs, an aging workforce, and improve automated operations.
Countless producers must ensure that flaws and anomalies remain under constant scrutiny. It is far easier to use computer vision since it delivers high-quality image data for higher quality analysis.
It’s not only about obtaining data in computer vision; it’s also about appropriately labeling it so that AI systems can learn from it. In the future, computer vision may help annotate data for more precise data analysis.
There’s no getting around the fact that 2D Inspection has its limits. With 3D Inspection, companies can more efficiently monitor and evaluate their systems, improving the accuracy and speed of examinations in general.
Anomaly detection has shown to be an effective method for spotting mistakes in financial transactions. Experts refer to it as a future trend in computer vision. When properly trained, machine learning-based models excel in detecting abnormalities in payment processes and preventing possible fraud.
Anomaly detection now offers an extra layer of security and lowers the chance of being hacked while completing a payment. It not only helps to enhance overall operations, but it also helps to provide exceptional services to consumers and end-users.