Technology Innovation Institute's (TII) Directed Energy Research Center (DERC) is integrating machine learning (ML) techniques into signal processing to accelerate research. One project used convolutional neural networks to predict COVID-19 pneumonia from chest x-rays with 97.5% accuracy. DERC researchers also demonstrated that ML-based signal and image processing can retrieve up to 68% of text information from electromagnetic emanations. Why it matters: This adoption of ML for signal processing at TII highlights the potential for advanced AI techniques to enhance research and security applications in the UAE.
KAUST has appointed Dr. Tony Chan, former president of HKUST and KAUST board member, as its new president, effective September 1, 2018. Chan's background is in computational mathematics with interests including image processing, computer vision, physical circuit design and computational brain mapping. He has been a close partner of KAUST since 2007 and a member of the KAUST Board of Trustees since 2011. Why it matters: Chan's leadership is expected to contribute to KAUST's role in achieving Saudi Arabia's Vision 2030 objectives and addressing global challenges.
KAUST's Visual Computing Center (VCC) is researching computer vision, image processing, and machine learning, with applications in self-driving cars, surveillance, and security. Professor Bernard Ghanem is working on teaching machines to understand visual data semantically, similar to how humans perceive the world. Self-driving cars use visual sensors to interpret traffic signals and detect obstacles, while computer vision also assists governments and corporations with security applications like facial recognition and detecting unattended luggage. Why it matters: Advancements in computer vision at KAUST can contribute to innovations in autonomous vehicles and enhance security measures in the region.
MBZUAI researchers presented a new approach to video analysis at ICCV in Paris, led by Syed Talal Wasim. The approach builds on still image processing techniques like focal modulation to analyze spatial and temporal information in video separately. It aims to improve temporal aggregation while avoiding the computational complexity of transformers. Why it matters: This research advances video understanding in computer vision by offering a more efficient method for temporal modeling, crucial for applications like activity recognition and video surveillance.
KAUST President Tony Chan received an honorary degree from the University of Waterloo in recognition of his contributions to society. Chan has strong ties to the University through the HKUST-UW research program which funded collaborative research projects. Chan is a globally recognized mathematician and leader in computational models for image processing. Why it matters: Recognition of KAUST's leadership on the global stage helps promote its research and educational initiatives in the region.
Researchers have reportedly developed an artificial intelligence system capable of deblurring photographs. This AI aims to enhance image clarity by using advanced algorithms to reconstruct sharper images from blurry inputs. The technology could significantly improve visual quality across various applications where image capture is prone to blur. Why it matters: This development contributes to the broader field of computer vision and image processing, offering potential applications in areas from surveillance to professional photography.
An artificial intelligence system has been developed that can reconstruct human faces from images affected by motion blur. This technology leverages advanced algorithms to reverse the blurring effect, enhancing facial clarity and detail. The system aims to improve image quality in various applications where motion artifacts are common. Why it matters: This advancement holds significant potential for applications in forensics, security surveillance, and improving consumer photography by recovering lost detail in images.