Visual AI, computer vision, imaging and cameras, robotics & automation, depth sensing, forensic and expert image analysis, media cryptography
Systems design, architecture, HW/ SOC/ FPGA, software development, embedded systems, apps, libraries, optimizations for accuracy, power, performance
Competitive analysis, market research, IP portfolio analysis, patent generation and IP development
Krig Research is a pioneer in visual AI, computer vision, machine learning, advanced imaging, and robotics systems, providing complete solutions for clients ranging across a wide range of governments and industries, world-wide.
We work hard to win your trust and confidence is priority #1. An ongoing business relationship and continued business are mutually beneficial, so every effort is made to understand your requirements and provide the best possible solution within your project parameters.
A free initial consultation is available on request. Krig Research provides complete engineering services to complete any visual computing project. In addition, we can add intelligence to your business via competitive analysis, patent portfolio development, product positioning, and industry trends.
The NeuroMatrix(tm) system contains a working model of the visual cortex of the human brain, including models of the eyes, early visual processing centers, and higher level reasoning centers. Capable of learning precise signatures of individual objects.
The NeuroTarget(tm) system locates targets in the visible light spectrum, therefore is capable of surviving common electronic warfare countermeasures which affect radar-based systems.
The massive project to learn visual DNA and visual genomes. Companion open source code and basic applications for the book "Synthetic Vision using Volume Learning and Visual DNA".
One of the most complete resource texts on computer vision. Download a complimentary copy of the 500 page classic from the Embedded Vision Alliance or APRESS.
This 653-page textbook edition in English from Springer-Verlag has also been translated into Chinese, and is updated with a comprehensive survey about deep learning, DNNs and RNNs.
A working model of the human visual system is described, as a first step towards synthetic vision systems and artificial visual intelligence within the visual genome foundation, from De Gruyter Pre