Why Use Low-Code Platforms for Computer Vision Application Development

Intelligent application and software development is the ultimate need for many businesses to succeed. However, designing and deploying such solutions takes significant time and resources. Especially, developing Computer Vision applications is a highly-challenging process for enterprises, since it is accompanied by several technological and research problems.

However, low-code platforms offer enterprises the ability to create complex Computer Vision applications using pre-tailored modules/components. The intuitive interface of low-code platforms suppresses time-intensive programming techniques and allows Computer Vision engineers to launch solutions that have the potential to disrupt business.

Understanding Computer Vision Applications

Computer Vision is a branch of Artificial Intelligence technology that allows systems to acquire insightful information by analyzing visual elements such as videos and photos. The insights gathered by systems are subsequently used to perform automated actions. In short, AI gives systems the capability to ‘think’ with data, whereas Computer Vision empowers them to ‘perceive’ the information.

Computer Vision app development is the process of creating automated solutions that can understand visual data similar to humans. These applications will extract visual data, manage it, and evaluate the outcomes using advanced software programs.

Also Read - Breaking Barriers: Assessing the Revolutionary Impact of Low-Code on Application Development

Why Low-Code for Computer Vision App Development

Low-Code platforms are helpful for enterprises to accelerate their Computer Vision app development projects and simplify the installation process. Since the AI models, infrastructure, and frameworks needed for Computer Vision apps is already available, low-code platforms facilitate faster development, testing, and scaling of solutions. Also, the rapid app development empowered by low-code platforms maximizes the business value of Computer Vision solutions and lessens time-to-market.

Some of the standard pre-tailored models offered by low-code platforms for Computer Vision app development include:

• Image Classification - Engineers can use basic image classification models from low-code platforms to precisely predict the type of object placed in an image.
• Object Detection - This model uses advanced image classification techniques to identify, assess, and count objects in visual input and determine their accurate class, along with their tagging.
• Object Tracking - Another Computer Vision model offered by many low-code platforms is Object tracking. By integrating this model in apps, tracking of objects in real-time can be done in order to avoid inaccuracies and follow the defined compliance rules or standards.
• Semantic Segmentation - This model not just helps in identifying the classes in an image, instead it categorizes each pixel of an image to determine what objects it contains.

By hiring developers from the low-code app development company, enterprises can speed up their Computer Vision app experiments and projects. Developers effortlessly incorporate different approaches and prototype multiple versions. Also, developers can rapidly test new applications without the need to invest in costly infrastructure.

Also Read - CTOs Take a Note: Low-Code is the Solution for Developer Burnout

Types of Computer Vision App Development With Low-Code Platforms

Healthcare Training Apps

Though Computer Vision is largely helpful in medical diagnosis, many healthcare service providers are leveraging this technology to build apps for medical skill training. The traditional approach of training surgeons and acquiring skills through hands-on practice results in adverse and antithetical outcomes. Instead, by using low-code platforms, healthcare firms can build simulation-based training platforms with Computer Vision technology as the core.

This way, service providers can allow trainees to improve their surgical skills before treating the patients in real-time. It enables them to acquire detailed opinions and valuation of their performance. Also, it creates better awareness for trainees about patient care and safety before actually treating them. Computer Vision-based training apps can also be used to evaluate the quality of the surgery by measuring the activity level, and time spent by trainees in specific areas, and classifying hectic movements.

Manufacturing Error Detection

Building Computer Vision-powered applications is the need of the hour for several manufacturing enterprises that deal with massive product and component assembly. These solutions can carry out redundant manufacturing tasks that the workforce struggles with. Manufacturers looking to embark on the industry 4.0 revolution should use low-code platforms to build and deploy Computer Vision applications to perform completely streamlined product assembly and management operations.

In addition, low-coded Computer Vision applications acquire real-time data from cameras and use Machine Learning algorithms to analyze huge data streams. This way, manufacturers can identify the defects easily based on the established quality standards and determine the deviation percentage. Also, the hindrances in the production cycle can be easily spotted. Overall, manufacturing and production processes can be made error-free with Computer Vision applications.

Retail Buyer Analysis

By developing Computer Vision-based customer analysis applications, retailers can identify in-store buyers’ patterns and interests. This includes the traffic capture rate and directs shoppers’ paths around the store. Customer analysis applications also help retailers understand which promotions create a huge impact among buyers and analyze the interaction between customers and associates, thereby providing better transparency into in-store retail engagement. Accordingly, retailers can launch personalized interaction and marketing campaigns.

Without connecting additional cameras, it’s possible for customer analysis applications to process the video stream. Low-Code application development platforms enable retailers to build such applications using Computer Vision and deep learning algorithms. The availability of pre-designed modules for traffic and footfall analysis in low-code platforms allow customer analysis applications to process video streams in real-time.

Also Read - 5 Key Low-Code Trends and Predictions for 2023 and Beyond

Summing Up

The best part of low-code platforms is that enterprises can build intelligent solutions by leveraging innovative technologies like Computer Vision in a minimal turnaround time. The intuitive development interface allows Computer Vision engineers to build low-code solutions with a quick return on investment.