In today’s world, the ability to extract meaningful insights from visual information has become increasingly valuable. Thanks to artificial intelligence (AI) improvements, specifically in computer vision, we have powerful tools to take advantage of visual intelligence. One of the tools is image classification, a technology that allows us to categorize and understand images based on visual features. Let’s explore the fascinating world of image classification and discover how it enables us to gain deeper insights from visual data and takes RPA processes to the next step.

Image classification is the process of training machines to recognize and categorize images into predefined classes or categories. Using machine learning algorithms, these models learn from labeled datasets and develop the ability to identify patterns and features that distinguish one category from another – allowing them to accurately classify new, unseen images based on their learned knowledge.

When it comes to RPA and using image classification technologies together, since RPA mimics human interactions, the ability to convert visual data into meaningful output advances RPA processes.

Applications of Image Classification in Robusta and Sample Use Cases

Combining AI technologies such as image classification into business processes can be challenging. Still, by connecting its users with embedded artificial intelligence technologies in a user-friendly no-code platform, Robusta ensures that non-value-added business processes are less human-oriented and more beneficial.

By “connecting”; it allows its users to train image classification models by creating labels, categories, and labeling training data according to their needs and integrate such powerful AI technologies into their RPA processes easily.

The applications of image classification are vast and span across various industries. Let’s take a look at a few use cases:

Quality Control in Manufacturing: In the manufacturing industry, image classification technology is used to control products if they are damaged or defective preshipping. According to research done in one of the biggest manufacturing companies in the world, for every 100 products sold, 1 to 3 of them will be returned because they are defective. So, according to that data, when the orders and returned products are calculated yearly, the return rate will vary between %1 and %3, which is an extra transportation cost for manufacturers. So, using image classification to control millions of products before shipping to the customer would decrease the return rate, so the transportation cost dramatically.
Work Safety in Construction Sites: In the industries such as construction, work safety is vital, but sometimes it can be neglected. So, image classification technology is used in construction sites to detect employees who are not dressed according to work safety (hard hats, vests, etc.) and warn them.

Example Process: Safety Compliance Check Using Image Classification with Robusta RPA

As an example process, using Robusta RPA and image classification feature, robots automatically check whether the employees in a factory are equipped following the occupational safety procedure. For example, the robot scans the images of workers if they are wearing helmets. Robots can provide information to the company’s occupational safety specialist, thus ensuring that the company is not penalized regarding occupational health and safety.

Conclusion

In conclusion, image classification is a powerful tool that can be used to gain deeper insights from visual data and take RPA processes to the next level. We expect to see even more innovative and efficient RPA processes as image classification technology evolves.