scholarly journals Systolic Nanofabrication of Super-Resolved Photonics and Biomimetics

Nanomaterials ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 2418
Author(s):  
Konstantina Papachristopoulou ◽  
Nikolaos A. Vainos
Keyword(s):  
Thermal Treatment ◽  
Three Dimensional ◽  
Super Resolution ◽  
Porous Solid ◽  
Solid Skeleton ◽  
Surface Features ◽  
Alternative Concept ◽  
The Future ◽  
Nanoscale Patterns

Systolic nanofabrication is demonstrated via conformal downsizing of three-dimensional micropatterned monolithic master-casts made of extremely nanoporous aerogel and xerogel materials. The porous solid skeleton collapses by thermal treatment, generating miniaturized replicas, which preserve the original stereometric forms and incorporate minified nanoscale patterns. Paradigmatic holographic and biomimetic nanoarchitectures are conformally downsized by ~4×, yielding subwavelength surface features of less than ~150 nm. The operations demonstrate the super-resolution capabilities of this alternative concept and its potential evolution to an innovative nanotechnology of the future.

Virtual laparoscopy: Initial experience with three-dimensional ultrasonography to characterize hepatic surface features

2013 ◽  
Vol 82 (6) ◽  
pp. 929-934 ◽  
Author(s):  
Tadashi Sekimoto ◽  
Hitoshi Maruyama ◽  
Takayuki Kondo ◽  
Taro Shimada ◽  
Masanori Takahashi ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Initial Experience ◽  
Surface Features

scholarly journals Three-dimensional super-resolution imaging for fluorescence emission difference microscopy

AIP Advances ◽  
2015 ◽  
Vol 5 (8) ◽  
pp. 084901 ◽  
Author(s):  
Shangting You ◽  
Cuifang Kuang ◽  
Shuai Li ◽  
Xu Liu ◽  
Zhihua Ding
Keyword(s):  
Three Dimensional ◽  
Fluorescence Emission ◽  
Super Resolution ◽  
Resolution Imaging

Super-resolution imaging using a three-dimensional metamaterials nanolens

2010 ◽  
Vol 96 (2) ◽  
pp. 023114 ◽  
Author(s):  
B. D. F. Casse ◽  
W. T. Lu ◽  
Y. J. Huang ◽  
E. Gultepe ◽  
L. Menon ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Super Resolution ◽  
Resolution Imaging

scholarly journals Programming the shape-shifting of flat soft matter: from self-rolling/self-twisting materials to self-folding origami

2016 ◽  
Vol 3 (6) ◽  
pp. 536-547 ◽  
Author(s):  
S. Janbaz ◽  
R. Hedayati ◽  
A. A. Zadpoor
Keyword(s):  
Soft Matter ◽  
Three Dimensional ◽  
Complex Surface ◽  
Surface Features

Rational programming of the shape-shifting behavior of flat materials (possibly decorated with complex surface features) to create complex three-dimensional structures.

Current and Future Three-Dimensional LSI Integration Technology by “chip on chip”, “chip on wafer” and “wafer on wafer”

2006 ◽  
Vol 970 ◽  
Author(s):  
Manabu Bonkohara ◽  
Makoto Motoyoshi ◽  
Kazutoshi Kamibayashi ◽  
Mitsumasa Koyanagi
Keyword(s):  
Three Dimensional ◽  
Process Time ◽  
Future Technology ◽  
Sensor Device ◽  
Research Level ◽  
Key Technologies ◽  
The Future ◽  
Chip Size ◽  
On Chip ◽  
Chip Chip

ABSTRACTRecently the development of three dimensional LSI (3D-LSI) has been accelerated and its stage has changed from the research level or limited production level to the investigation level with a view to mass production. This paper describes the current and the future 3D-LSI technologies which we have considered and imagined. The current technology is taken our Chip Size Package (CSP) for sensor device, for instance. In the future technology, there are the five key technologies are described. And considering con and pro of the current 3D LSI stacked approach, such as CoC (Chip on Chip), CoW (Chip on Wafer) and WoW (Wafer on Wafer), We confirmed that CoW combined with Super-Smart-Stack (SSS™) technology will shorten the process time per chip at the same level as WoW approach and is effective to minimize process cost.

A Fast View Synthesis Implementation Method for Light Field Applications

2021 ◽  
Vol 17 (4) ◽  
pp. 1-20
Author(s):  
Wei Gao ◽  
Linjie Zhou ◽  
Lvfang Tao
Keyword(s):  
Neural Networks ◽  
Light Field ◽  
Three Dimensional ◽  
Super Resolution ◽  
View Synthesis ◽  
Compact Representation ◽  
Light Weight ◽  
Computationally Efficient ◽  
Full Resolution ◽  
Time Systems

View synthesis (VS) for light field images is a very time-consuming task due to the great quantity of involved pixels and intensive computations, which may prevent it from the practical three-dimensional real-time systems. In this article, we propose an acceleration approach for deep learning-based light field view synthesis, which can significantly reduce calculations by using compact-resolution (CR) representation and super-resolution (SR) techniques, as well as light-weight neural networks. The proposed architecture has three cascaded neural networks, including a CR network to generate the compact representation for original input views, a VS network to synthesize new views from down-scaled compact views, and a SR network to reconstruct high-quality views with full resolution. All these networks are jointly trained with the integrated losses of CR, VS, and SR networks. Moreover, due to the redundancy of deep neural networks, we use the efficient light-weight strategy to prune filters for simplification and inference acceleration. Experimental results demonstrate that the proposed method can greatly reduce the processing time and become much more computationally efficient with competitive image quality.

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