Pneumonia, an infection in the lungs that causes difficulty breathing, is most commonly diagnosed through chest X-rays. Typically, those chest X-rays are read by radiologists, but workforce shortages mean that in the future, it could be harder to get a diagnosis in a timely manner.Pneumonia, an infection in the lungs that causes difficulty breathing, is most commonly diagnosed through chest X-rays. Typically, those chest X-rays are read by radiologists, but workforce shortages mean that in the future, it could be harder to get a diagnosis in a timely manner.[#item_full_content]

Johns Hopkins researchers have developed an efficient new method to turn blurry images into clear, sharp ones. Called Progressively Deblurring Radiance Field (PDRF), this approach deblurs images 15 times faster than previous methods while also achieving better results on both synthetic and real scenes.Johns Hopkins researchers have developed an efficient new method to turn blurry images into clear, sharp ones. Called Progressively Deblurring Radiance Field (PDRF), this approach deblurs images 15 times faster than previous methods while also achieving better results on both synthetic and real scenes.[#item_full_content]

Imagine yourself glancing at a busy street for a few moments, then trying to sketch the scene you saw from memory. Most people could draw the rough positions of the major objects like cars, people, and crosswalks, but almost no one can draw every detail with pixel-perfect accuracy. The same is true for most modern computer vision algorithms: They are fantastic at capturing high-level details of a scene, but they lose fine-grained details as they process information.Imagine yourself glancing at a busy street for a few moments, then trying to sketch the scene you saw from memory. Most people could draw the rough positions of the major objects like cars, people, and crosswalks, but almost no one can draw every detail with pixel-perfect accuracy. The same is true for most modern computer vision algorithms: They are fantastic at capturing high-level details of a scene, but they lose fine-grained details as they process information.[#item_full_content]

Researchers led by Prof. Xie Chengjun and Assoc. Prof. Zhang Jie from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences have introduced an innovative pan-sharpening method to improve remote sensing images.Researchers led by Prof. Xie Chengjun and Assoc. Prof. Zhang Jie from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences have introduced an innovative pan-sharpening method to improve remote sensing images.[#item_full_content]

In a recent article published in the National Science Review, researchers have proposed a new operator learning framework called PIANO. PIANO uses self-supervised learning to extract representations containing physical invariants from partial differential equations (PDEs) systems with different physical mechanisms, thereby extending the generalization ability of neural operators to various physics scenarios.In a recent article published in the National Science Review, researchers have proposed a new operator learning framework called PIANO. PIANO uses self-supervised learning to extract representations containing physical invariants from partial differential equations (PDEs) systems with different physical mechanisms, thereby extending the generalization ability of neural operators to various physics scenarios.[#item_full_content]

To discourage the inefficient manual invention and configuration of new metaheuristic optimization algorithms, a research team at IRIDIA, the artificial intelligence laboratory of the Université Libre de Bruxelles, studied the literature and outlined the strengths of automatic approaches to the design of metaheuristics, especially compared to the many redundant—and at times outlandish—metaphor-based metaheuristics.To discourage the inefficient manual invention and configuration of new metaheuristic optimization algorithms, a research team at IRIDIA, the artificial intelligence laboratory of the Université Libre de Bruxelles, studied the literature and outlined the strengths of automatic approaches to the design of metaheuristics, especially compared to the many redundant—and at times outlandish—metaphor-based metaheuristics.[#item_full_content]

Machine learning is a branch of artificial intelligence (AI) and computer science that focuses on the use of data and algorithms to allow computers to learn without explicitly being programmed. While discussions surrounding AI algorithms, such as ChatGPT and other generative models, are taking place at all levels of society, the machine learning capabilities of quantum computers are still somewhat unexplored.Machine learning is a branch of artificial intelligence (AI) and computer science that focuses on the use of data and algorithms to allow computers to learn without explicitly being programmed. While discussions surrounding AI algorithms, such as ChatGPT and other generative models, are taking place at all levels of society, the machine learning capabilities of quantum computers are still somewhat unexplored.[#item_full_content]

If a robot traveling to a destination has just two possible paths, it needs only to compare the routes’ travel time and probability of success. But if the robot is traversing a complex environment with many possible paths, choosing the best route amid so much uncertainty can quickly become an intractable problem.If a robot traveling to a destination has just two possible paths, it needs only to compare the routes’ travel time and probability of success. But if the robot is traversing a complex environment with many possible paths, choosing the best route amid so much uncertainty can quickly become an intractable problem.[#item_full_content]

Computers work in digits—0s and 1s, to be exact. Their calculations are digital; their processes are digital; even their memories are digital. All of which require extraordinary power resources. As we look to the next evolution of computing and developing neuromorphic or “brain-like” computing, those power requirements are unfeasible.Computers work in digits—0s and 1s, to be exact. Their calculations are digital; their processes are digital; even their memories are digital. All of which require extraordinary power resources. As we look to the next evolution of computing and developing neuromorphic or “brain-like” computing, those power requirements are unfeasible.[#item_full_content]

Room-scale virtual reality (VR) is one where users explore a VR environment by physically walking through it. The technology provides many benefits, given its highly immersive experience. Yet the drawback is that it requires large physical spaces. It can also lack haptic feedback when touching objects.Room-scale virtual reality (VR) is one where users explore a VR environment by physically walking through it. The technology provides many benefits, given its highly immersive experience. Yet the drawback is that it requires large physical spaces. It can also lack haptic feedback when touching objects.[#item_full_content]