REHABILITATION  |  MEDICAL ELECTRODES  |  BRAIN COMPUTER INTERFACE  |  MACHINE LEARNING  |  EMBEDDED COMPUTER VISION  |  NEW MATERIALS  |  ENERGY

EMBEDDED COMPUTER VISION
By employing advanced algorithms, machine learning techniques, and pattern recognition, Computer Vision holds immense potential across various industries, reshaping the way we interact with our visual world.

The technology
Computer vision is an interdisciplinary field that encompasses various techniques for acquiring, processing, analyzing, and interpreting digital images. It involves the extraction of valuable information from visual data in the real world, which is then transformed into numerical or symbolic data that can be used to make decisions. Essentially, computer vision is about teaching machines to recognize, understand, and respond to visual information the way humans do.​

This field has the potential to revolutionize many industries and applications, from self-driving cars and robotics to medical imaging and surveillance systems. Advances in this field are constantly pushing the boundaries of what machines can achieve with visual data, making it a fascinating and dynamic area of research and innovation.
Our commitment
At Henesis, we are embedding Computer Vision techniques into portable equipment to shape technologies and solutions for the detection of anomalies such as corrosion and rust, missing parts, or spots, especially where the inspection of the object or subject is made difficult by limitations in accessibility or specific skills.

Transforming industrial surveys with autonomous rust detection, through our AI-enabled drone system.

The Henesis Computer Vision team tested our new technology during automated drone flights. The onboard AI analysed video streams in real-time, capturing high-resolution images at areas with significant rust. This innovative approach ensures accurate rust detection on large structures, even in hard-to-reach areas.

Our collaboration with ABzero has been instrumental in demonstrating the versatility of this technology. By testing it in various settings such as naval and building contexts, we have effectively showcased its applicability across different industries and environments.

Learn more
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