Z Advanced Computing, Inc. (ZAC) of Potomac, MD announced on August 27 that it is funded by the US Air Force, to use ZAC's detailed 3D image recognition technology, based on Explainable-AI, for drones (unmanned aerial vehicle or UAV) for aerial image/object recognition. ZAC is the first to demonstrate Explainable-AI, where various attributes and details of 3D (three dimensional) objects can be recognized from any view or angle. "With our superior approach, complex 3D objects can be recognized from any direction, using only a small number of training samples," said Dr. Saied Tadayon, CTO of ZAC. "For complex tasks, such as drone vision, you need ZAC's superior technology to handle detailed 3D image recognition." "You cannot do this with the other techniques, such as Deep Convolutional Neural Networks, even with an extremely large number of training samples. That's basically hitting the limits of the CNNs," continued Dr. Bijan Tadayon, CEO of ZAC.
Software star-up, Z Advanced Computing, Inc. (ZAC), has received funding from the U.S. Air Force to incorporate the company's 3D image recognition technology into unmanned aerial vehicles (UAVs) and drones for aerial image and object recognition. ZAC's in-house image recognition software is based on Explainable-AI (XAI), where computer-generated image results can be understood by human experts. ZAC – based in Potomac, Maryland – is the first to demonstrate XAI, where various attributes and details of 3D objects can be recognized from any view or angle. "With our superior approach, complex 3D objects can be recognized from any direction, using only a small number of training samples," says Dr. Saied Tadayon, CTO of ZAC. "You cannot do this with the other techniques, such as deep Convolutional Neural Networks (CNNs), even with an extremely large number of training samples. That's basically hitting the limits of the CNNs," adds Dr. Bijan Tadayon, CEO of ZAC.
The recognition of objects is one of the main goals for computer vision research. Some of the applications include: the automation on the assembly line, inspection of integrated circuit chips to detect defects in them, security in face and fingerprint recognition, medical diagnosis and detection of abnormal cells that may indicate cancer, remote sensing for automated recognition of possible hostile terrain to generate maps and aids for the visually impaired of mechanical guide dogs. However, 3D object recognition has been one of the challenging processes facing computer vision systems. One Maryland-based startup may finally have the answer to the problem. The startup, Z Advanced Computing, announced today that it has made technical and scientific breakthrough towards Machine Learning and Artificial Intelligence (AI), where the various attributes and details of 3D (three dimensional) objects can be recognized from any view or angle, using its novel General-AI techniques.
The platform will be the integral part of Image Search Engine for Image Referral Network and Image Ad Network, to automate generation and placement of highly-relevant targeted ads based on images in a large scale for the first time in the industry. ZAC's AI Discovery platform can also be used for other types of images, data, or objects, e.g., clothing, purse, accessories, medical images, satellite images, and biometrics. ZAC has an impressive team of scientists and developers. The software development is headed by Saied Tadayon, a veteran software developer and scientist, who got PhD from Cornell at age 23. One of ZAC's inventors is Prof. Lotfi A. Zadeh ("The Father of Fuzzy Logic"), a pioneer computer scientist at U.C. Berkeley.
A team of researchers from Maryland say they've invented a general artificial intelligence way for machines to identify and process 3-D images that doesn't require humans to go through the tedium of inputting specific information that accounts for each and every instance, scenario, difference, change and category that could crop up. But stay with me, layperson. This is actually a huge deal for the technology sector -- a massive step for the case of general AI versus specific AI. And once fine-tuned, this development will have the power to shape and change how everyone from police and intelligence officials to retail marketers and medical professionals go about their daily business. Currently, neural networks, defined as those computing systems that are aimed at mimicking how humans think and make decisions, are only as good as the information that's inputted.