Recent years have witnessed great advances in applying deep learning to improve fluorescence microscopy imaging. However, enhancing the fidelity of image restoration networks and improving their ...

Designing surfaces that precisely control how light behaves at the nanoscale is tricky. Optical Fourier surfaces, which are ...

Abstract: Image super resolution focuses on increasing the spatial resolution of low-quality images and enhancing their visual quality. Since the image degradation process is unknown in real-life ...

Deep learning is a subset of machine learning that uses multi-layer neural networks to find patterns in complex, unstructured data like images, text, and audio. What sets deep learning apart is its ...

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...

Abstract: Unsupervised domain adaptation (UDA) addresses the domain shift problem by transferring knowledge from labeled source domain data (e.g. CT) to unlabeled target domain data (e.g. MRI). While ...

Crop segmentation, the process of identifying crop regions in images, is fundamental to agricultural monitoring tasks such as yield prediction, pest detection, and growth assessment. Traditional ...

Google has added a 'Guided Learning' mode in Gemini to promote deeper understanding of complex topics and concepts. It's available for free to all Gemini users. You can upload your course materials, ...