Results 51 to 60 of about 22,393,926 (290)
Joint High Dynamic Range Imaging and Super-Resolution From a Single Image
IEEE Access, 2019 This paper presents a new framework for jointly enhancing the resolution and the dynamic range of an image, i.e., simultaneous super-resolution (SR) and high dynamic range imaging (HDRI), based on a convolutional neural network (CNN).
Jae Woong Soh, Jae Sung Park, Nam Ik Cho
doaj +1 more source
FEBS Letters, EarlyView.Plasma membranes contain dynamic nanoscale domains that organize lipids and receptors. Because viruses operate at similar scales, this architecture shapes early infection steps, including attachment, receptor engagement, and entry. Using influenza A virus and HIV‐1 as examples, we highlight how receptor nanoclusters, multivalent glycan interactions ...
Jan Schlegel, Christian Sieben
wiley +1 more source
High-fidelity colour reproduction for high-dynamic-range imaging [PDF]
, 2010 The aim of this thesis is to develop a colour reproduction system for high-dynamic-range (HDR) imaging. Classical colour reproduction systems fail to reproduce HDR images because current characterisation methods and colour appearance models fail to ...
Kim, M.H.
core
FEBS Letters, EarlyView.We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace +6 more
wiley +1 more source
Maximizing precision over extended unambiguous range for TOF range imaging systems [PDF]
, 2010 The maximum unambiguous range for time-of-flight range imaging systems is inversely proportional to the chosen modulation frequency. However, increasing the unambiguous range by decreasing the modulation frequency will generally also degrade the range ...
Payne, Andrew D. +7 more
core +1 more source
Low Dynamic Range Solutions to the High Dynamic Range Imaging Problem
Journal of Measurement Science and Instrumentation, 2010 While capturing a real world scene using a common digital camera,due to limitations of the sensor dynamic range,we will not be able to capture the entire dynamic range of the scene.This problem is evident while capturing a picture of a scene which has ...
Shanmuganathan RAMAN, Subhasis CHAUDHURI
doaj
Model for High Dynamic Range Imaging System Using Hybrid Feature Based Exposure Fusion
Journal of Intelligent Systems, 2020 The luminous value is high for many natural scenes, which causes loss of information and occurs in dark images. The High Dynamic Range (HDR) technique captures the same objects or scene for multiple times in different exposure and produces the images ...
Kiran Bagadi Ravi +2 more
doaj +1 more source
From mice to humans—divergent strategies for intestinal homeostasis and regeneration
FEBS Letters, EarlyView.Recent advances such as organoid genome editing, xenotransplantation, imaging, and whole‐genome sequencing have enabled direct studies of human intestinal stem cells (ISCs). These studies reveal species‐specific features, including slower ISC proliferation, distinct injury responses, slower somatic mutation accumulation in humans, and an inverse ...
Keiko Ishikawa +2 more
wiley +1 more source
High Dynamic Velocity Range Particle Image Velocimetry Using Multiple Pulse Separation Imaging
Sensors, 2010 The dynamic velocity range of particle image velocimetry (PIV) is determined by the maximum and minimum resolvable particle displacement. Various techniques have extended the dynamic range, however flows with a wide velocity range (e.g., impinging jets ...
Tadhg S. O’Donovan, Tim Persoons
doaj +1 more source
Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source