Results 151 to 160 of about 2,554 (206)

Nanoscale Depth Profiling of Optoelectronic Devices Using Deep-UV LIBS. [PDF]

ACS Omega
Surampudi A, Gupta MC.
europepmc   +1 more source

Protocol for short-term in vitro propagation of patient-derived group 4 medulloblastoma MBT375 tumor cells. [PDF]

STAR Protoc
Custers S, Venugopal C, Singh SK.
europepmc   +1 more source

Integrating Machine Learning with Flow-Imaging Microscopy for Automated Monitoring of Algal Blooms. [PDF]

Environ Sci Technol
Khan F, Gincley B, Busch A, Tolofari DL, Norton JW, Varga E, McKay RM, Fuentes-Cabrera M, Slawecki T, Pinto AJ.   +9 more
europepmc   +1 more source

Nitrogen-Vacancy Centers in Fluorescent Nanodiamonds: Emerging Applications from Healthcare Diagnostics to Semiconductor Metrology. [PDF]

Acc Chem Res
Chang HC.
europepmc   +1 more source

Pushing the resolution limit of coherent diffractive imaging. [PDF]

Light Sci Appl
Liu L, Du J, Zhuang B, Gong M, Liu J, Gu H, Liu S.   +6 more
europepmc   +1 more source

Selecting the optimal focus measure for autofocusing and depth-from-focus

IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998
—A method is described for selecting the optimal focus measure with respect to gray-level noise from a given set of focus measures in passive autofocusing and depth-from-focus applications.
Jenn-kwei Tyan, Murali Subbarao
exaly   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Autofocusing for tissue microscopy

Image and Vision Computing, 1993
Abstract This paper describes the implementation of autofocusing for tissue microscopy. We first investigate the suitability of several criterion functions for the evaluation of image sharpness. Since tissue sections are invariably stained, we also discuss the selection of the colour component on which autofocusing will be performed.
Yeo, T., Ong, S., Jayasooriah, Sinniah, R.   +3 more
openaire   +2 more sources

A survey on ISAR autofocusing techniques

2004 International Conference on Image Processing, 2004. ICIP '04., 2005
Over many years of research, several ISAR autofocusing techniques have been proposed. Today, we can divide them into two main categories: parametric and non-parametric techniques. The prominent point processing and the phase gradient algorithm are two classical examples of non-parametric techniques, whereas the more recent image contrast and entropy ...
BERIZZI, FABRIZIO, MARTORELLA, MARCO, B. HAYWOOD, DALLE MESE, ENZO, S. BRUSCOLI   +4 more
openaire   +3 more sources

Autofocusing‐based phase correction

Magnetic Resonance in Medicine, 2018
PurposePhase artifacts due to B0 inhomogeneity can severely degrade the quality of MR images. The artifacts are particularly prominent in long‐TE scans and usually appear as ghosting and blur. We propose a retrospective phase correction method based on autofocusing.
Loktyushin, A., Ehses, P., Schölkopf, B., Scheffler, K.   +3 more
openaire   +5 more sources

Multifocus autofocusing Airy beam

Journal of the Optical Society of America A, 2017
We propose a multifocus autofocusing Airy beam (MAAB) by modifying the frequency spectrum of a symmetric Airy beam (SAB) with a Gaussian band elimination filter. Unlike the original SAB, there are four off-axis foci at the autofocusing plane of the MAAB. The MAAB has a better abruptly autofocusing property than the original SAB.
Tong, Li, Fei, Zi, Kaikai, Huang, Xuanhui, Lu   +3 more
openaire   +2 more sources