Search Results - (( data estimation method algorithm ) OR ( data visualization system algorithm ))*
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1
Parallel visualization approach of a 3D heart model
Published 2008“…The basis of this technique is that the location of an object is estimated using an estimation algorithm and the radio frequency (RF) fingerprint database as a reference. …”
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2
EEG-based brain source localization using visual stimuli
Published 2016“…According to the spatial resolution provided, the algorithms are categorized as either low resolution methods or high resolution methods. …”
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3
Subsea Pipeline Corrosion Estimation by Restoring and Enhancing Degraded Underwater Images
Published 2018“…The enhanced colours in the imaging data helps in corrosion estimation process. The image restoration and enhancement algorithm are tested on both experimentally collected as well as publicly available hazy underwater images. …”
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4
Subsea Pipeline Corrosion Estimation by Restoring and Enhancing Degraded Underwater Images
Published 2018“…The enhanced colours in the imaging data helps in corrosion estimation process. The image restoration and enhancement algorithm are tested on both experimentally collected as well as publicly available hazy underwater images. …”
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5
Segmentation of Magnetic Resonance Brain Images Using Watershed Algorithm
Published 2004“…The proposed technique based on the watershed algorithm, which is applied to the gradient magnitude of the MRI data. …”
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6
Generalized Subspace Approach for Measurements of Visual Evoked Potentials
Published 2009“…The results of fifty real patient data further confirm that both GSAs are better estimators compared to the other studied techniques. …”
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7
Generalized Subspace Approach for Measurement of Latencies in Visual Evoked Potentials
Published 2010“…The results of fifty real patient data further confirm that both GSAs are better estimators compared to the other studied techniques. …”
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8
A Subspace Approach with Pre-whitening for Measurements of Latencies in Visual Evoked Potentials
Published 2011“…The performance of SAPW in estimating VEP latencies has been assessed using simulated data at SNR ranging from 0 to -11 dB, and real patient data gathered in a hospital. …”
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9
Visual feedback–based heading control of autonomous underwater vehicle for pipeline corrosion inspection
Published 2017“…There are two parts of this study: the first part includes the heading control of the underwater vehicle using visual feedback to follow the pipeline, whereas the second part involves underwater image enhancement and dehazing using wavelet-based fusion for corrosion estimation. The visual feedback and corrosion estimation rely on the same image data during the inspection of the pipeline, hence, reducing the complexity of the overall algorithm. …”
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10
Hybrid sampling and random forest machine learning approach for software detect prediction
Published 2019“…Matplotlib, and PyPlot are used for graph and data visualization respectively. The hybrid sampling method and Random Forest (RF) algorithms achieved the highest prediction accuracy about 93.26% by showing its superiority.…”
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11
A Salient Based Bag of Visual Word model (SBBoVW): improvements toward difficult object recognition and object location in image retrieval
Published 2016“…One is to introduce a new approach, which is a Salient Based Bag of Visual Word model (SBBoVW) to recognize difficult objects that have had low accuracy in previous methods. This method integrates SIFT features of the original and salient parts of pictures and fuses them together to generate better codebooks using bag of visual word method. …”
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12
Development of river water level estimation from surveillance cameras for flood monitoring system using deep learning techniques
Published 2022“…By integrating the estimated water level with a 3D model developed from LiDAR data, flood simulation was performed. …”
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13
Deep Reinforcement Learning For Control
Published 2021“…The complete project is carried out in the CARLA simulator to determine how to operate in discrete action space using Deep Reinforcement Learning (DRL) algorithms. Gathering and evaluating a large amount of data is time and effortintensive. …”
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14
Unsupervised monocular depth estimation with multi-scale structural similarity powered loss function / Ali Kohan
Published 2020“…Depth Estimation refers to a set of techniques and algorithms that aim to obtain a representation of spatial information of a scene. …”
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15
Evaluation of cracks and disintegrations using close-range digital photogrammetry and image processing technique
Published 2005“…With an automated digital image processing technique of pavement distress analysis, more areas can be surveyed and the collected data can be analysed quickly. Furthermore, the automated method can improve the objectivity, accuracy, and consistency of distress survey data. …”
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16
Spatial variations prediction in carbonate porosity using artificial neural network: Subis Limestones, Sarawak, Malaysia
Published 2019“…Several models have been developed to visualize the pore network systems of carbonate rocks. …”
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17
Spatial variations prediction in carbonate porosity using artificial neural network: Subis Limestones, Sarawak, Malaysia
Published 2019“…Several models have been developed to visualize the pore network systems of carbonate rocks. …”
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Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying
Published 2019“…In order to reduce the training time and computational cost of the algorithm, Principal Components Analysis (PCA) pretraining strategy is deployed to obtain data adaptive filter banks. …”
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19
Development Of Distributed Grid-Based Hydrological Model And Floodplain Inundation Management System
Published 2008“…The rainfall-runoff hydrological modelling was implemented in MATLAB 7.0. The system has integrated GIS, RS, DEM, data management capability and a dynamic basin model within a common Windows environment. …”
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20
ERNN: A biologically inspired feedforward neural network to discriminate emotion from EEG signal
Published 2014“…The accuracy of the proposed neural network is compared with various feature extraction methods and feedforward learning algorithms. The results showed that the highest accuracy is achieved when using the proposed neural network with a type of radial basis function.…”
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