Results 61 to 70 of about 742,455 (317)

Enteropathogenic E. coli shows delayed attachment and host response in human jejunum organoid‐derived monolayers compared to HeLa cells

FEBS Letters, EarlyView.
Enteropathogenic E. coli (EPEC) infects the human intestinal epithelium, resulting in severe illness and diarrhoea. In this study, we compared the infection of cancer‐derived cell lines with human organoid‐derived models of the small intestine. We observed a delayed in attachment, inflammation and cell death on primary cells, indicating that host ...
Mastura Neyazi, Pilar Samperio Ventayol, Natalie Burkard, Nicolas Schlegel, Carmen Aguilar, Sina Bartfeld   +5 more
wiley   +1 more source

Image Generation From Layout

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Accepted to CVPR 2019 (Oral)
Bo Zhao, Lili Meng, Weidong Yin, Leonid Sigal   +3 more
openaire   +2 more sources

Leveraging a Vision Transformer and Adversarial Unsupervised Domain Adaptation to Generate the NIR Band on Out-of-Domain VHR RGB

IEEE Access
The accessibility of very-high-resolution Remote Sensing (RS) near-infrared (NIR) imagery before the 2010s is limited. In addition, public annotated image datasets often used as benchmarks contain only RGB information.
Viktoria Kristollari, Vassilia Karathanassi   +1 more
doaj   +1 more source

Training Set Enlargement Using Binary Weighted Interpolation Maps for the Single Sample per Person Problem in Face Recognition

Applied Sciences, 2020
We propose a method of enlarging the training dataset for a single-sample-per-person (SSPP) face recognition problem. The appearance of the human face varies greatly, owing to various intrinsic and extrinsic factors.
Yonggeol Lee, Sang-Il Choi
doaj   +1 more source

Organoids in pediatric cancer research

FEBS Letters, EarlyView.
Organoid technology has revolutionized cancer research, yet its application in pediatric oncology remains limited. Recent advances have enabled the development of pediatric tumor organoids, offering new insights into disease biology, treatment response, and interactions with the tumor microenvironment.
Carla Ríos Arceo, Jarno Drost
wiley   +1 more source

A Review on Generative AI For Text-To-Image and Image-To-Image Generation and Implications To Scientific Images

CoRR
This review surveys the state-of-the-art in text-to-image and image-to-image generation within the scope of generative AI. We provide a comparative analysis of three prominent architectures: Variational Autoencoders, Generative Adversarial Networks and Diffusion Models.
Zineb Sordo, Eric Chagnon, Daniela Ushizima   +2 more
openaire   +2 more sources

Quantum generative adversarial networks with dual generators

Machine Learning: Science and Technology
Quantum generative adversarial networks (QGANs) have demonstrated strong capabilities in tasks like synthetic data generation and detecting anomalies. Recent developments have increasingly integrated traditional machine learning techniques to boost the ...
Quangong Ma, Chaolong Hao, NianWen Si, Dan Qu   +3 more
doaj   +1 more source

SceEmoNet: A Sentiment Analysis Model with Scene Construction Capability

Applied Sciences
How do humans analyze the sentiments embedded in text? When attempting to analyze a text, humans construct a “scene” in their minds through imagination based on the text, generating a vague image.
Yi Liang, Dongfang Han, Zhenzhen He, Bo Kong, Shuanglin Wen   +4 more
doaj   +1 more source

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

FEBS 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, Shin Morioka, Junko Sasaki, Takehiko Sasaki   +3 more
wiley   +1 more source

Decoupled Latent Diffusion Model for Enhancing Image Generation

IEEE Access
Latent Diffusion Models have emerged as an efficient alternative to conventional diffusion approaches by compressing high-dimensional images into a lower-dimensional latent space using a Variational Autoencoder (VAE) and performing diffusion in that ...
Hyun-Tae Choi, Kensuke Nakamura, Byung-Woo Hong   +2 more
doaj   +1 more source