Search results for "artificial intelligence"

Fuzzy sigmoid kernel for support vector classifiers

2004

This Letter proposes the use of the fuzzy sigmoid function presented in (IEEE Trans. Neural Networks 14(6) (2003) 1576) as non-positive semi-definite kernel in the support vector machines framework. The fuzzy sigmoid kernel allows lower computational cost, and higher rate of positive eigenvalues of the kernel matrix, which alleviates current limitations of the sigmoid kernel.

Use of hierarchical Bayesian framework in MTS studies to model different causes and novel possible forms of acquired MTS

2015

Abstract: An integrative account of MTS could be cast in terms of hierarchical Bayesian inference. It may help to highlight a central role of sensory (tactile) precision could play in MTS. We suggest that anosognosic patients, with anesthetic hemisoma, can also be interpreted as a form of acquired MTS, providing additional data for the model.

Colour assessment of milk and milk products using computer vision system and colorimeter

2021

Abstract A computer vision system (CVS) and a colorimeter were compared for their abilities to measure the colour of twenty-seven different milks and milk products. The frequency of similarity test showed that CVS-generated colour chips were similar to the actual sample colour in all trials (100%). The CVS-obtained colours were found to be more similar to the colour of sample visualised on the monitor, compared with colorimeter-generated colour chips, with values of 83.3–100.0% depending on the milk product. The third test showed that there was difference between colour measured by CVS and the colorimeter; colorimeter readings resulted in a darker and yellower colour based on average L∗a∗b∗…

Normalization 2.0: A longitudinal analysis of German online campaigns in the national elections 2002–9

2011

This article examines the functional, relational and discursive dimensions of the normalization thesis in one study, for both Web 1.0 and Web 2.0 features, in a longitudinal design. It is based on a quantitative content and structural analysis of German party websites in the national elections between 2002 and 2009. The results show that the normalization thesis holds true in all its dimensions over time and in the Web 2.0 era: parties still focus on the top-down elements of information provision and delivery while interactive options are scarce. The digital divide between parliamentary and non-parliamentary parties has narrowed over time, but remains visible for all online functions in 200…

Perceptual image quality assessment using a normalized Laplacian pyramid

2016

Visualization of Memory Map Information in Embedded System Design

2018

Data compression is a common requirement for displaying large amounts of information. The goal is to reduce visual clutter. The approach given in this paper uses an analysis of a data set to construct a visual representation. The visualization is compressed using the address ranges of the memory structure. This method produces a compressed version of the initial visualization, retaining the same information as the original. The presented method has been implemented as a Memory Designer tool for ASIC, FPGA and embedded systems using IP-XACT. The Memory Designer is a user-friendly tool for model based embedded system design, providing access and adjustment of the memory layout from a single v…

Automating statistical diagrammatic representations with data characterization

2017

The search for an efficient method to enhance data cognition is especially important when managing data from multidimensional databases. Open data policies have dramatically increased not only the volume of data available to the public, but also the need to automate the translation of data into efficient graphical representations. Graphic automation involves producing an algorithm that necessarily contains inputs derived from the type of data. A set of rules are then applied to combine the input variables and produce a graphical representation. Automated systems, however, fail to provide an efficient graphical representation because they only consider either a one-dimensional characterizat…

Mesh Visual Quality based on the combination of convolutional neural networks

2019

Blind quality assessment is a challenging issue since the evaluation is done without access to the reference nor any information about the distortion. In this work, we propose an objective blind method for the visual quality assessment of 3D meshes. The method estimates the perceived visual quality using only information from the distorted mesh to feed pre-trained deep convolutional neural networks. The input data is prepared by rendering 2D views from the 3D mesh and the corresponding saliency map. The views are split into small patches of fixed size that are filtered using a saliency threshold. Only the salient patches are selected as input data. After that, three pre-trained deep convolu…

Multiple Classifiers and Data Fusion for Robust Diagnosis of Gearbox Mixed Faults

2019

Detection and isolation of single and mixed faults in a gearbox are very important to enhance the system reliability, lifetime, and service availability. This paper proposes a hybrid learning algorithm, consisting of multilayer perceptron (MLP)- and convolutional neural network (CNN)-based classifiers, for diagnosis of gearbox mixed faults. Domain knowledge features are required to train the MLP classifier, while the CNN classifier can learn features itself, allowing to reduce the required knowledge features for the counterpart. Vibration data from an experimental setup with gearbox mixed faults is used to validate the effectiveness of the algorithms and compare them with conventional metho…

Fusion of CNN and sparse representation for threat estimation near power lines and poles infrastructure using aerial stereo imagery

2021

Abstract Fires or electrical hazards and accidents can occur if vegetation is not controlled or cleared around overhead power lines, resulting in serious risks to people and property and significant costs to the community. There are numerous blackouts due to interfering the trees with the power transmission lines in hilly and urban areas. Power distribution companies are facing a challenge to monitor the vegetation to avoid blackouts and flash-over threats. Recently, several methods have been developed for vegetation monitoring; however, existing methods are either not accurate or could not provide better disparity map in the textureless region. Moreover, are not able to handle depth discon…