Results 41 to 50 of about 475,373 (270)

Image Style Transfer Using Deep Learning

open access: yesInternational Journal for Research in Applied Science and Engineering Technology, 2022
Abstract: In order to increase the quality of the composite image throughout the image style transfer process. This study presents an improved style loss function-based image style transfer method: the improved Gram matrix calculates the inner product of the feature map and the spatial transformation map, and then the new style loss function.
Aniket Landge   +4 more
openaire   +1 more source

An improved defocusing adaptive style transfer method based on a stroke pyramid.

open access: yesPLoS ONE, 2023
Image style transfer aims to assign a specified artist's style to a real image. However, most existing methods cannot generate textures of various thicknesses due to the rich semantic information of the input image.
Jianfang Cao   +3 more
doaj   +2 more sources

Artistic style transfer for videos and spherical images

open access: yes, 2018
Manually re-drawing an image in a certain artistic style takes a professional artist a long time. Doing this for a video sequence single-handedly is beyond imagination.
Brox, Thomas   +2 more
core   +1 more source

Bringing Impressionism to Life with Neural Style Transfer in Come Swim

open access: yes, 2017
Neural Style Transfer is a striking, recently-developed technique that uses neural networks to artistically redraw an image in the style of a source style image. This paper explores the use of this technique in a production setting, applying Neural Style
Joshi, Bhautik   +2 more
core   +1 more source

Coherent Online Video Style Transfer

open access: yes, 2017
Training a feed-forward network for fast neural style transfer of images is proven to be successful. However, the naive extension to process video frame by frame is prone to producing flickering results. We propose the first end-to-end network for online
Chen, Dongdong   +4 more
core   +1 more source

Mapping the evolution of mitochondrial complex I through structural variation

open access: yesFEBS Letters, EarlyView.
Respiratory complex I (CI) is crucial for bioenergetic metabolism in many prokaryotes and eukaryotes. It is composed of a conserved set of core subunits and additional accessory subunits that vary depending on the organism. Here, we categorize CI subunits from available structures to map the evolution of CI across eukaryotes. Respiratory complex I (CI)
Dong‐Woo Shin   +2 more
wiley   +1 more source

Cross Modal Facial Image Synthesis Using a Collaborative Bidirectional Style Transfer Network

open access: yesIEEE Access, 2022
In this paper, we present a novel collaborative bidirectional style transfer network based on generative adversarial network (GAN) for cross modal facial image synthesis, possibly with large modality gap.
Nizam Ud Din   +4 more
doaj   +1 more source

Audio style transfer

open access: yes, 2018
'Style transfer' among images has recently emerged as a very active research topic, fuelled by the power of convolution neural networks (CNNs), and has become fast a very popular technology in social media.
Duong, Ngoc   +3 more
core   +1 more source

Spatiotemporal and quantitative analyses of phosphoinositides – fluorescent probe—and mass spectrometry‐based approaches

open access: yesFEBS Letters, EarlyView.
Fluorescent probes allow dynamic visualization of phosphoinositides in living cells (left), whereas mass spectrometry provides high‐sensitivity, isomer‐resolved quantitation (right). Their synergistic use captures complementary aspects of lipid signaling. This review illustrates how these approaches reveal the spatiotemporal regulation and quantitative
Hiroaki Kajiho   +3 more
wiley   +1 more source

Fast Continuous Structural Similarity Patch Based Arbitrary Style Transfer

open access: yesApplied Sciences, 2019
Style transfer is using a pair of content and style images to synthesize a stylized image which has both the structure of the content image and the style of style image. Existing optimization-based methods are limited in their performance.
Bing Wu, Youdong Ding, Qingshuang Dong
doaj   +1 more source

Home - About - Disclaimer - Privacy