Results 51 to 60 of about 1,186,551 (242)
DualGAN: Unsupervised Dual Learning for Image-to-Image Translation
Conditional Generative Adversarial Networks (GANs) for cross-domain image-to-image translation have made much progress recently. Depending on the task complexity, thousands to millions of labeled image pairs are needed to train a conditional GAN. However,
Gong, Minglun +3 more
core +1 more source
Unsupervised Image-to-Image Translation Networks
Unsupervised image-to-image translation aims at learning a joint distribution of images in different domains by using images from the marginal distributions in individual domains. Since there exists an infinite set of joint distributions that can arrive the given marginal distributions, one could infer nothing about the joint distribution from the ...
Liu, Ming-Yu, Breuel, Thomas, Kautz, Jan
openaire +2 more sources
Few-Shot Unsupervised Image-to-Image Translation [PDF]
Unsupervised image-to-image translation methods learn to map images in a given class to an analogous image in a different class, drawing on unstructured (non-registered) datasets of images. While remarkably successful, current methods require access to many images in both source and destination classes at training time.
Liu, Ming-Yu +7 more
openaire +4 more sources
By dawn or dusk—how circadian timing rewrites bacterial infection outcomes
The circadian clock shapes immune function, yet its influence on infection outcomes is only beginning to be understood. This review highlights how circadian timing alters host responses to the bacterial pathogens Salmonella enterica, Listeria monocytogenes, and Streptococcus pneumoniae revealing that the effectiveness of immune defense depends not only
Devons Mo +2 more
wiley +1 more source
Mechanisms of Generative Image-to-Image Translation Networks
Existing image-to-image translation models often rely on complex architectures with multiple loss terms, making them difficult to interpret and computationally expensive.
Guangzong Chen +4 more
doaj +1 more source
AFF‐UNIT: Adaptive feature fusion for unsupervised image‐to‐image translation
The task of image‐to‐image translation is to generate images closer to the target domain style while preserving the significant features of the original image. This paper contends an adaptive feature fusion method for unsupervised image translation.
Yuqiang Li +3 more
doaj +1 more source
The role and implications of mammalian cellular circadian entrainment
At their most fundamental level, mammalian circadian rhythms occur inside every individual cell. To tell the correct time, cells must align (or ‘entrain’) their circadian rhythm to the external environment. In this review, we highlight how cells entrain to the major circadian cues of light, feeding and temperature, and the implications this has for our
Priya Crosby
wiley +1 more source
A Diffusion Model Translator for Efficient Image-to-Image Translation
Applying diffusion models to image-to-image translation (I2I) has recently received increasing attention due to its practical applications. Previous attempts inject information from the source image into each denoising step for an iterative refinement, thus resulting in a time-consuming implementation.
Mengfei Xia +4 more
openaire +3 more sources
Crosstalk between the ribosome quality control‐associated E3 ubiquitin ligases LTN1 and RNF10
Loss of the E3 ligase LTN1, the ubiquitin‐like modifier UFM1, or the deubiquitinating enzyme UFSP2 disrupts endoplasmic reticulum–ribosome quality control (ER‐RQC), a pathway that removes stalled ribosomes and faulty proteins. This disruption may trigger a compensatory response to ER‐RQC defects, including increased expression of the E3 ligase RNF10 ...
Yuxi Huang +8 more
wiley +1 more source
Consistency-Aware Map Generation at Multiple Zoom Levels Using Aerial Image
The multilevel tiled map service is widely used and serves as a kind of digital infrastructure. These map tiles are usually rendered from vector data, whose update needs to walk or drive with professional equipment to check every point of interest.
Linwei Chen, Zheng Fang, Ying Fu
doaj +1 more source

