The rapid development of computer technology not only makes it possible to process enormous amounts of diverse data, but also makes it possible to use complex and diverse methods for collecting, analyzing, and classifying data.
Today, object detection technology based on artificial intelligence, machine learning, and computer vision is used in many industries and scientific disciplines, such as psychology, biology, medicine, and marketing,
It can be used for marketing, analysis, human concept support, or decision aid.
Object detection solutions can be widely used in practice. Here are some of the examples:
Technical check-up: Automating quality control in manufacturing. Problem-solving for detecting defects, as well as their classification.
Medical diagnostics: Diagnosing diseases based on the analysis of cardiograms, MRI results, X-rays, etc.
Letter recognition: In conjunction with the mobile camera it can support the operation of handwriting input devices.
Robotics: The use of detection algorithms in robotics is a necessary process since the work must perceive and visualize the outside world, and to do this, have machine vision devices.
Security systems: In security systems, the use of detection solutions is justified primarily in the context of identification and the granting of appropriate access rights. Identification can be done by voice, fingerprints, etc.
Mobile devices: In mobile devices, such technologies can help in the recognition of objects using the camera in real-time. For example, owners of iOS 15 can not only identify different objects in the photo but also get additional information about them. Intelligent mechanisms can recognize works of art, landmarks, natural objects, or animals located in the photo.
Marketing: The analysis of the visual context of a recognized logo provides useful insight for building a communication strategy and evaluating the effectiveness of an advertising campaign.
Object detection solutions kit is a longstanding and cutting-edge product from Computools that uses advanced artificial neural networks and computer vision algorithms to detect objects in video/photo.
Instead of developing and implementing from scratch, this pre-made solution will reduce development time by up to 30% and costs by 70%.
Since their developers are tied to multiple solution kits based on their experience in certain frameworks and technologies, the risk of bugs is reduced to 95%.
The fact that it can be customized to multiple industries and business niches makes it a no-nonsense choice if you want to achieve significant breakthroughs in object recognition functionality and get sustainable results in a short time.