Results 311 to 320 of about 3,028,783 (361)
Some of the next articles are maybe not open access.

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

European Conference on Computer Vision, 2016
We consider image transformation problems, where an input image is transformed into an output image. Recent methods for such problems typically train feed-forward convolutional neural networks using a per-pixel loss between the output and ground-truth ...
Justin Johnson   +2 more
semanticscholar   +1 more source

Super Resolution for Smartphones

Proceedings of the 13th International Joint Conference on e-Business and Telecommunications, 2016
Smartphones were developed as an advanced communication tool. Currently they are used in various applications. The display is one of the most important features in smartphones. Compared with television (TV) and cinema screens the display size of a smartphone is small.
Seiichi Gohshi   +4 more
openaire   +1 more source

Super resolution: an overview

Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05., 2005
Abstract : Super-resolution algorithms produce a single high-resolution image from a set of several, low-resolution images of the desired scene. The low-resolution frames are shifted differently with respect to the high resolution frame with subpixel increments. This paper presents first a theoretical overview of super-resolution algorithms.
Christos Papathanassiou, Maria Petrou
openaire   +1 more source

Accelerating the Super-Resolution Convolutional Neural Network

European Conference on Computer Vision, 2016
As a successful deep model applied in image super-resolution (SR), the Super-Resolution Convolutional Neural Network (SRCNN) [1, 2] has demonstrated superior performance to the previous hand-crafted models either in speed and restoration quality. However,
Chao Dong, Chen Change Loy, Xiaoou Tang
semanticscholar   +1 more source

Super-resolution of mammograms

2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2010
High-quality mammography is the most effective technology presently available for breast cancer screening. High resolution mammograms usually lead to more accurate diagnoses; however, they require large doses of radiation, which may have harmful effects.
Jun Zheng 0010   +2 more
openaire   +1 more source

Super-resolution in MRI

Proceedings IEEE International Symposium on Biomedical Imaging, 2003
In 2D multislice MRI, the resolution in the slice direction is often worse than the in-plane resolution. For certain diagnostic imaging applications, isotropic resolution is necessary but true 3D acquisition methods are not practical. In this case, if the imaging volume is acquired two or more times, with small spatial shifts between acquisitions ...
Hayit Greenspan   +3 more
openaire   +1 more source

Resolution and super‐resolution

Microscopy Research and Technique, 2017
AbstractMany papers have claimed the attainment of super‐resolution, i.e. resolution beyond that achieved classically, by measurement of the profile of a feature in the image. We argue that measurement of the contrast of the image of a dark bar on a bright background does not give a measure of resolution, but of detection sensitivity.
openaire   +2 more sources

Super-resolution writing

Nature Chemistry, 2019
The in situ, nanoscale positioning of a single molecule below the diffraction limit remains a challenge for chemists. Now, two approaches show how this can be accomplished through a combination of super-resolution microscopy and photo-inducible crosslinking chemistry.
Limin, Xiang, Ke, Xu
openaire   +2 more sources

Dual Aggregation Transformer for Image Super-Resolution

IEEE International Conference on Computer Vision, 2023
Transformer has recently gained considerable popularity in low-level vision tasks, including image super-resolution (SR). These networks utilize self-attention along different dimensions, spatial or channel, and achieve impressive performance.
Zheng Chen   +5 more
semanticscholar   +1 more source

Super-Sampling by Learning-Based Super-Resolution

International Journal of Computational Science and Engineering, 2018
In this paper, we present a novel problem of intelligent image processing, which is how to infer a finer image in terms of intensity levels for a given image. We explain the motivation for this effort and present a simple technique that makes it possible to apply the existing learning-based super-resolution methods to this new problem.
Ping Du, Jinhuan Zhang, Jun Long
openaire   +1 more source

Home - About - Disclaimer - Privacy