The natural protein universe is vast, and yet, going beyond and designing new proteins not observed in nature can yield new ...

Advancements in biomedical technologies have significantly facilitated the diagnosis and monitoring of diseases. Nonetheless, traditional diagnostic ...

Researchers at the Indian Institute of Science (IISc) and the Qatar Science and Technology Research Center (QSRTC) have ...

Motivated by the relationship between motion and blur, we propose a motion-aware feature learning framework for dynamic scene deblurring through multi-task learning. Our multi-task framework ...

A group of scientists led by researchers from the University of New South Wales (UNSW) in Australia has developed a novel deep-learning method for denoising outdoor electroluminescence (EL) images ...

Recent advances in artificial intelligence have significantly improved spectral data analysis. In this study, we used unsupervised machine learning to classify chemical compounds based on infrared (IR ...

Inspired by a fact that different images are degraded in dissimilar ways, we propose to explore image-level degradation knowledge to perform deblurring for complex blur images. We thereby introduce a ...

Better deblurring results are achieved by this decomposition, which not only makes the estimated image more regular but also helps to reduce high-frequency noise. Our method aims to overcome the ...

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 ...

Recent advances in image data proccesing through deep learning allow for new optimization and performance-enhancement schemes for radiation detectors and imaging hardware. This enables radiation ...