53‐2: Directional variations of specular reflections from displays

2021 ◽  
Vol 52 (1) ◽  
pp. 729-732
Author(s):  
Michael E. Becker
Keyword(s):  
Specular Reflections

Der fatale Blick in den Spiegel – Zum Zusammenhang von Medialität und Reflexivität

2010 ◽  
Vol 55 (2) ◽  
pp. 87-99 ◽  
Author(s):  
Oliver Jahraus
Keyword(s):  
18Th Century ◽  
Specular Reflections ◽  
The Subject ◽  
Literature And Film

Der Beitrag untersucht den Zusammenhang von Reflexivität und Medialität (das, was ein Medium zum Medium macht), indem er die Idee der Reflexion an den konkreten Formen von Spiegelungen in Literatur und Film wie zum Beispiel Doppelgänger oder Figurenspaltungen darstellt. Dabei zeigt sich, daß jedes Medium autoreflexiv verfasst ist und daß die Vorstellung von Subjektivität seit dem 18. Jahrhundert selbst auf diesem Zusammenspiel von Reflexivität und Medialität beruht. Das Subjekt gilt demnach als reflexiver Effekt der Medialität, wie es an einer Betrachtung von Foucaults berühmter Meninas-Interpretation nachverfolgt werden kann.<br><br>This article analyses the relation between reflexivity and mediality (what makes a medium a medium) by presenting concrete situations of optical and specular reflections in literature and film, such as doubles (Doppelgänger) and split figures. Thus it can be shown that since the 18th century every medium is self-reflexive and that the concept of subjectivity has its basis in the interplay of reflexivity and mediality. The subject is an effect of medialitity as may be demonstrated by a new recapitulation of Foucault’s famous Meninas-interpretation.

scholarly journals Using spatial-temporal ensembles of convolutional neural networks for lumen segmentation in ureteroscopy

2021 ◽  
Author(s):  
Jorge F. Lazo ◽  
Aldo Marzullo ◽  
Sara Moccia ◽  
Michele Catellani ◽  
Benoit Rosa ◽  
...  
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
State Of The Art ◽  
Automatic Segmentation ◽  
Temporal Information ◽  
Invasive Technique ◽  
Dice Similarity Coefficient ◽  
Specular Reflections ◽  
Lumen Segmentation ◽  
Previous State

Abstract Purpose Ureteroscopy is an efficient endoscopic minimally invasive technique for the diagnosis and treatment of upper tract urothelial carcinoma. During ureteroscopy, the automatic segmentation of the hollow lumen is of primary importance, since it indicates the path that the endoscope should follow. In order to obtain an accurate segmentation of the hollow lumen, this paper presents an automatic method based on convolutional neural networks (CNNs). Methods The proposed method is based on an ensemble of 4 parallel CNNs to simultaneously process single and multi-frame information. Of these, two architectures are taken as core-models, namely U-Net based in residual blocks ($$m_1$$ m 1 ) and Mask-RCNN ($$m_2$$ m 2 ), which are fed with single still-frames I(t). The other two models ($$M_1$$ M 1 , $$M_2$$ M 2 ) are modifications of the former ones consisting on the addition of a stage which makes use of 3D convolutions to process temporal information. $$M_1$$ M 1 , $$M_2$$ M 2 are fed with triplets of frames ($$I(t-1)$$ I ( t - 1 ) , I(t), $$I(t+1)$$ I ( t + 1 ) ) to produce the segmentation for I(t). Results The proposed method was evaluated using a custom dataset of 11 videos (2673 frames) which were collected and manually annotated from 6 patients. We obtain a Dice similarity coefficient of 0.80, outperforming previous state-of-the-art methods. Conclusion The obtained results show that spatial-temporal information can be effectively exploited by the ensemble model to improve hollow lumen segmentation in ureteroscopic images. The method is effective also in the presence of poor visibility, occasional bleeding, or specular reflections.

Tomographic resolution limits for diffraction imaging

2015 ◽  
Vol 3 (1) ◽  
pp. SF15-SF20 ◽  
Author(s):  
Yunsong Huang ◽  
Dongliang Zhang ◽  
Gerard T. Schuster
Keyword(s):  
Numerical Simulations ◽  
Diffraction Data ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Specular Reflections ◽  
Data Resolution ◽  
Resolution Limits ◽  
Diffraction Imaging ◽  
Noise Ratio

We derived formulas for the tomographic resolution limits [Formula: see text] of diffraction data. Resolution limits exhibited that diffractions can provide twice or more the tomographic resolution of specular reflections and therefore led to more accurate reconstructions of velocities between layers. Numerical simulations supported this claim in which the tomogram inverted from diffraction data was noticeably more resolved compared to that inverted from specular data. The specular synthetics were generated by sources on the surface, and the diffraction data were generated by buried diffractors. However, this advantage is nullified if the intensity and signal-to-noise ratio of the diffractions are much less than those of the pervasive specular reflections.

Interpretation value of diffractions and sub-specular reflections – applications on the Zhao Dong field

First Break ◽  
2017 ◽  
Vol 35 (2149) ◽  
Author(s):  
Michael Pelissier ◽  
Tijmen Jan Moser ◽  
Changhua Yu ◽  
Jing Lang ◽  
Ioan Sturzu ◽  
...  
Keyword(s):  
Specular Reflections
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