One of the coolest branches of AI, computer vision trends, and predictions will boost the industry by 2022.

Computer vision is a fascinating branch of artificial intelligence with a lot of practical applications. There will be a flood of billion-dollar computer vision businesses in the next years, with the industry estimated to reach US$49 billion by 2022. Computer vision's major objective is to enable computers to understand the environment through sight and make decisions based on that understanding. In practice, this technology enables the automation and enhancement of human vision, resulting in a wide range of applications.

Ensure Your Safety

There's no getting around it: industrial businesses must continually consider their employees' safety. This is especially true in the event of a pandemic when computer vision can assist in detecting whether personnel is wearing masks or other protective equipment. Computer vision can assist in ensuring safety and maintaining social distance.

Edge Computing

Edge computing is one of the most talked-about computer vision topics. For those unfamiliar with edge computing, it allows data to be processed and analyzed more quickly at the site of collection. This enables greater in-the-moment analysis, insight, and calculation. Edge computing may also aid in the detection of abnormalities and the reduction of latency, making it suitable for businesses that are prone to network failures.

Robots with Vision Guidance

Companies use robots for a variety of purposes, but vision-guided robots are particularly useful in the manufacturing industry. Robots can assist businesses in anticipating growing labor expenses, an aging workforce, and improving automated processes.

Quality Analysis

Countless producers must guarantee that faults and abnormalities are continually checked. It is considerably easier to do so with computer vision because computer vision provides for high-quality picture data for better quality analysis.

Visibility of the Supply Chain

Understanding and strengthening the supply chain is one of the most significant developments in the manufacturing industry. Manufacturers can increase profitability and save expenses by using computer vision.

Data Annotation 

When it comes to computer vision, it's not only about gathering data; it's also about correctly annotating it so that AI systems can learn from it. Moving the future, computer vision can assist annotate data for more accurate data analysis.

3D Inspection

There's no denying that 2D examination has its limitations. Companies may more efficiently monitor and examine their systems with 3D inspection, which improves the accuracy and speed of examinations in general.

Anomaly Detection

Anomaly detection has shown to be a useful tool for detecting errors in financial transactions. It's called a future trend in computer vision by experts. Machine learning-based models, when correctly trained, excel in detecting anomalies in payment processes and preventing potential fraud. Today, anomaly detection adds an extra layer of protection and reduces the risk of being hacked while making a payment. It not only aids in the improvement of overall operations but also the provision of extraordinary services to consumers and end-users.

Computer Vision in Banking

In the realm of banking, computer vision is a game-changer. OCR technology, which is a subset of computer vision, is a Swiss army knife for capturing and extracting data quickly and efficiently. Technology makes it easier for bank employees to manage massive amounts of data. OCR technology collects and extracts data from a variety of documents, relieving staff from time-consuming and laborious activities. Banks are increasingly implementing computer vision technology to improve client experiences and back-office procedures. Smile-to-pay facial scanning, micro-expression analysis with virtual-loan officers, conversational bots for simple servicing requests, and humanoid robots in branches to assist clients are all examples of how computer vision is utilized in the front office. Computer vision is used in the back office for biometric authentication and authorization, machine learning to identify fraud trends, cybersecurity threats, document scanning and processing, and real-time transaction analysis for risk management.

Computer Vision in Retail and E-commerce

Retail customization and consumer experience are evolving thanks to computer vision technologies. Nobody does it better than computer vision when it comes to providing relevant product recommendations. The more data you have and the more AI analyses it, the better the real-time service you can provide to your clients. The goal of the computer vision prediction engine is to propose product bundles that have been specifically selected for the customer. This high level of content customization not only enhances the user experience but also significantly boosts e-commerce and online retail sales. In the field of computer vision, visual search is a relatively new trend. The technology allows a customer to input an image of a product they like, and it subsequently displays comparable goods on the website. People no longer have to hunt for the appropriate phrases or spend hours looking for relevant information. Content-based image retrieval methods are used by visual search engines. In the realm of e-commerce, visual search allows customers to have a quick and easy purchasing experience. When a customer has no trouble identifying the correct product, they are more likely to purchase it.