Computer vision
Vision
Computer vision is focused on the extraction of meaningful information from digital imagery using computers and can be an extremely useful feature of any project that relies on an understanding of the surrounding environment. We’ve previously built vision systems for a bunch of interesting applications, e.g., inspection, pose estimation, classification, segmentation, and object detection and recognition.
Machine learning
Machine learning (ML) excels at cutting through noise in data and has proven especially effective in vision-based systems. Although traditional DIP can be a powerful tool in certain contexts, ML has become the de facto methodology. Having contributed to this field in an academic capacity, we’re confident that our state-of-the-art knowledge on this topic can be utilised to achieve your goals.
Edge devices
Small form factor single board computers (SBCs) with parallel computing capabilities help facilitate real-time, on the edge processing of ML and deep learning algorithms. These units let us build systems that operate as close to the originating source of data as possible, reducing overall reliance on networking.