Search results for "Mask"

Kalmbergin kartasto R V : List 10

1855

El Capitan as a Site for Male Healing from Trauma in Jeff Long’s The Wall and Tommy Caldwell’s The Push

2019

Nature and mountains are often represented as places of healing in literature and the media, especially for white, healthy, and middleclass men. However, discussions on nature and gender in relation to trauma are rare, and a specific discussion on the representation of male mountain climbers’ traumas is missing. In this article, we are interested in how nature, particularly the famous mountain El Capitan, is represented in Jeff Long’s novel “The Wall” (2006) and Tommy Caldwell’s memoir “The Push” (2017) as a specific spatial location of healing for male rock climbers, who at the same time are both victims of traumatic events and partially responsible for the development of those events. Mor…

Maskavas priekšpilsētas (Rīgā) attīstība no 19.gs. otrās puses līdz 1915.g

2017

Maģistra darba mērķis ir izpētīt Maskavas priekšpilsētas attīstības tendences no 19. gadsimta otrās puses līdz 1915. gadam, pievēršoties tajā esošās apbūves tendencēm un infrastruktūras pilnveides darbiem, saimnieciskajai un komercdarbībai, kā arī izmaiņām demogrāfiskajā situācijā. Darbā analizētas pārmaiņas, kuras piedzīvoja priekšpilsētas, Rīgas industrializācijas un modernizācijas kontekstā. Maskavas priekšpilsēta, kura veidojusies kā pilsētas daļa ar savu īpatnējo iedzīvotāju sastāvu un pilsētbūvniecisko veidolu, pēc pilsētas nocietinājumu sistēmas nojaukšanas pakāpeniski sāka iekļauties Rīgas saimnieciskajā un kultūras dzīvē, tajā pašā laikā turpinot saglabāt savu netipiskumu. Maskavas…

Multitemporal Cloud Masking in the Google Earth Engine

2018

The exploitation of Earth observation satellite images acquired by optical instruments requires an automatic and accurate cloud detection. Multitemporal approaches to cloud detection are usually more powerful than their single scene counterparts since the presence of clouds varies greatly from one acquisition to another whereas surface can be assumed stationary in a broad sense. However, two practical limitations usually hamper their operational use: the access to the complete satellite image archive and the required computational power. This work presents a cloud detection and removal methodology implemented in the Google Earth Engine (GEE) cloud computing platform in order to meet these r…

MODIS probabilistic cloud masking over the Amazonian evergreen tropical forests: a comparison of machine learning-based methods

2019

Amazonian tropical forests play a significant role in global water, carbon and energy cycles. Satellite remote sensing is presented as a feasible means in order to monitor these forests. In particu...

Loudness changes induced by a proximal sound: loudness enhancement, loudness recalibration, or both?

2007

The effect of a forward masker on the loudness of a target tone in close temporal proximity was investigated. Loudness matches between a target and a comparison tone at the same frequency were obtained for a wide range of target and masker levels. Contrary to the hypothesis by Scharf, Buus, and Nieder [J. Acoust. Soc. Am. 112, 807-810 (2002)], these matches could not be explained by an effect of the masker on the comparison loudness, which was measured by loudness matches between the comparison and a fourth tone separated in frequency from the comparison and the masker. The data thus demonstrate that a forward masker has an effect on the loudness of a proximal target. The results are compat…

Frequency Determined Homomorphic Unsharp Masking Algorithm on Knee MR Images

2005

A very important artifact corrupting Magnetic Resonance (MR) Images is the RF inhomogeneity, also called Bias artifact. The visual effect produced by this kind of artifact is an illumination variation which afflicts this kind of medical images. In literature a lot of works oriented to the suppression of this artifact can be found. The approaches based on homomorphic filtering offer an easy way to perform bias correction but none of them can automatically determine the cut-off frequency. In this work we present a measure based on information theory in order to find the frequency mentioned above and this technique is applied to MR images of the knee which are hardly bias corrupted.

Effects of Masking on Open-Circuit Voltage and Fill Factor in Solar Cells

2019

Guidelines for the correct measurement protocol of novel photovoltaic technologies such as perovskites are becoming more frequent in literature. This because, as will be confirmed in this perspective, it is not straightforward to correctly measure the efficiency parameters of these and many other novel solar cells. This is particularly the case for small area research devices which are prone to overestimate the short circuit current density, due to edge effects of various types. To reduce the inaccuracy of current density determination, the common recommended practice is to utilize masks with well‐defined apertures, often smaller than the device active area. Herein we show both experimental…

Design principles of chemiluminescence (CL) chemodosimeter for self-signaling detection: Luminol protective approach

2014

Chemiluminescence (CL) sensors can provide convenience and high sensitivity because they do not require an external excitation light source to produce a fluorescence signal. However, most CL based detection systems do not have a built-in self-signaling process, leading to inefficient and complex protocols due to the required multistep cascade reactions. Here, we develop a CL based sensory system with a built-in self-signaling feature by adapting the chemodosimeter concept. We found that a masking group incorporated to luminol efficiently suppresses the CL of luminol and that selective removal of the masking group by a target analyte can turn on the CL process, generating a sensitive fluores…

Convolutional Neural Networks for Multispectral Image Cloud Masking

2020

Convolutional neural networks (CNN) have proven to be state of the art methods for many image classification tasks and their use is rapidly increasing in remote sensing problems. One of their major strengths is that, when enough data is available, CNN perform an end-to-end learning without the need of custom feature extraction methods. In this work, we study the use of different CNN architectures for cloud masking of Proba-V multispectral images. We compare such methods with the more classical machine learning approach based on feature extraction plus supervised classification. Experimental results suggest that CNN are a promising alternative for solving cloud masking problems.