Search results for "Image."

A Novel Fast Volumetric Light Sheet Microscopy

2016

Fast noninvasive three-dimensional (3D) imaging is crucial for the quantitative understanding of highly dynamic biological processes. Over the last decades, several fluorescence microscopy techniques have been developed in order to provide a faster and deeper imaging of thick biological samples [1]. Within this framework, Light Sheet Fluorescence Microscopy (LSFM) has emerged as a powerful imaging tool for 3D imaging of thick samples ranging from single cells to entire animals [2,3].However, to obtain a 3D reconstruction either sample or microscope parts usually need to be moved limiting the acquisition speed and inducing possible interferences in volume recording. To solve this problem, he…

What Key Aspects Do ICOs Reveal About Their Businesses?

2020

AbstractBlockchain technologies disrupt industries by enabling decentralized and transactional data sharing across a network of untrusted participants, among others. Initial Coin Offerings (ICOs) are a novel form of crowdfunding through which hundreds of blockchain-enabled businesses manage to raise billions of dollars in total only in United States. However, there is a lack of understanding of the ICO phenomenon especially related to the business aspects. In this paper, we describe the results of an exploratory study of 91 ICOs and identify the key business model elements that ICOs reveal in their websites and whitepapers. Furthermore, we also note the immaturity and lack of transparency o…

Representation of the Wife Carrying World Championships in the English-language press

2012

A new methodology to estimate deformation of longitudinal safety barriers

2013

The correct sizing of storage areas in the port areas is aimed to optimizing the management of intermodal transport and to ensure efficiency and functionality to the entire port system. In this paper is proposed a simulation model for design the port storage areas taking into account many parameters like: the service time, the randomness of the arrivals process, the storage capacity in terms of TEU that can be stored (and handled) in the unit of time. The capacity of the terminal warehouse is determined by the interrelation between fixed and static parameters in the short period which are: i) the extension of the storage area; ii) the height of the overlapping batteries of container (define…

Ciudad imaginada: educación geográfica por medio de la fotografía

2022

"Ciudad imaginada: educación geográfica por medio de la fotografía”, es una apuesta por interpretar el papel de la subjetividad y el lenguaje en la construcción del conocimiento espacial y social. La tesis, que se inscribe en el Doctorado en Educación de la Universidad Pedagógica Nacional en Colombia y el Doctorado en Didácticas Específicas de la Universidad de Valencia en España (en régimen de co-tutela), da cuenta del trabajo teórico, metodológico y didáctico desarrollado en tres ciudades de Iberoamérica: Bogotá (Colombia), Valencia (España) y São Paulo (Brasil). El cuestionamiento que orienta la investigación se centra en la construcción de estrategias de enseñanza y aprendizaje de la ci…

What makes segmentation good? A case study in boreal forest habitat mapping

2013

Segmentation goodness evaluation is a set of approaches meant for deciding which segmentation is good. In this study, we tested different supervised segmentation evaluation measures and visual interpretation in the case of boreal forest habitat mapping in Southern Finland. The data used were WorldView-2 satellite imagery, a lidar digital elevation model (DEM), and a canopy height model (CHM) in 2 m resolution. The segmentation methods tested were the fractal net evolution approach (FNEA) and IDRISI watershed segmentation. Overall, 252 different segmentation methods, layers, and parameter combinations were tested. We also used eight different habitat delineations as reference polygons agains…

The Truth is Out There : Focusing on Smaller to Guess Bigger in Image Classification

2023

In Artificial Intelligence (AI) in general and in Machine Learning (ML) in particular, which are important and integral components of modern Industry 4.0, we often deal with uncertainty, e.g., lack of complete information about the objects we are classifying, recognizing, diagnosing, etc. Traditionally, uncertainty is considered to be a problem especially in the responsible use of AI and ML tools in the smart manufacturing domain. However, in this study, we aim not to fight with but rather to benefit from the uncertainty to improve the classification performance in supervised ML. Our objective is a kind of uncertainty-driven technique to improve the performance of Convolutional Neural Netwo…

Efficient contour-based annotation by iterative deep learning for organ segmentation from volumetric medical images

2022

Abstract Purpose Training deep neural networks usually require a large number of human-annotated data. For organ segmentation from volumetric medical images, human annotation is tedious and inefficient. To save human labour and to accelerate the training process, the strategy of annotation by iterative deep learning recently becomes popular in the research community. However, due to the lack of domain knowledge or efficient human-interaction tools, the current AID methods still suffer from long training time and high annotation burden. Methods We develop a contour-based annotation by iterative deep learning (AID) algorithm which uses boundary representation instead of voxel labels to incorp…

Kuvien maaseutu : maaseutumaisemakuvaston luomat mielikuvat suomalaisesta maaseutukulttuurista

2013

Glottal Source Features for Automatic Speech-Based Depression Assessment

2017

Depression is one of the most prominent mental disorders, with an increasing rate that makes it the fourth cause of disability worldwide. The field of automated depression assessment has emerged to aid clinicians in the form of a decision support system. Such a system could assist as a pre-screening tool, or even for monitoring high risk populations. Related work most commonly involves multimodal approaches, typically combining audio and visual signals to identify depression presence and/or severity. The current study explores categorical assessment of depression using audio features alone. Specifically, since depression-related vocal characteristics impact the glottal source signal, we exa…