This is a tensorflow implementation of "Fast and Accurate Image Super Resolution by Deep CNN with Skip Connection and Network in Network", a deep learning based Single-Image Super-Resolution (SISR) ...

The CNN is trained to reconstruct image regions where information has been lost due to sensor saturation, such as highlights and bright image features. This means that a standard 8-bit single exposed ...

Jake Paul speaks to CNN Sport about his big sporting plans for 2025 and motivations for building a platform for women’s ...

After converting BOLD signals to scalogram images using CWT, i.e., maps of wavelet coefficients at ... To the best of our knowledge, this is the first study of machine learning on the single-voxel ...

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Given the reduced size of our usable dataset, we employed single-image super-resolution to enhance image quality and effectively double our dataset size as a augmentation part of training data. For ...

Elon Musk Steps Up Efforts to Cull Federal Work Force Mr. Musk said federal workers must summarize their accomplishments for the week or be forced to leave, borrowing a tactic he used at his ...

This paper presents a machine learning pipeline for assessing burn severity and ... Attention Mapping (BAM), a saliency mapping method that leverages the trained CNN to accurately segment burn regions ...

Dan is a senior editor at Raw Story based in Colorado, producing and editing breaking political news. Dan previously worked as a news associate at The Associated Press in Philadelphia, and later ...