New research shows your brain may learn complex visual patterns without effort, reward, or feedback -- just by passively ...

3.2 Data pre-processing The background of the C. elegans images downloaded from Zenodo 15 is masked with black pixels. In some images the masking contains errors with background objects not masked out ...

CT metal artefact reduction (MAR) methods based on supervised deep learning are often troubled by domain gap between simulated training dataset and real-application dataset, i.e., methods trained on ...

Condensing the many physical variables defining a chemical system into a fixed-size array poses a significant challenge in the development of chemical Machine Learning (ML). Atom Centered Symmetry ...

Our unsupervised statistical approach is fast and effective for analyzing WSIs, with greatly improved scalability over attention-based deep learning methods. The high accuracy of SAMPLER-based ...

A.I. companies have an edge in blocking the creation and distribution of child sexual abuse material. They’ve seen how social media companies failed.

In this paper, we tackle a fully unsupervised super-resolution problem, i.e., neither paired images nor ground truth HR images. We assume that low resolution (LR) images are relatively easy to collect ...

Deep learning techniques have led to state-of-the-art image super resolution with natural images. Normally, pairs of high-resolution and low-resolution images are used to train the deep learning ...