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An HVS-Directed Neural-Network-Based Image Resolution Enhancement Scheme for Image Resizing
2007
IEEE transactions on fuzzy systems
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Bilinear interpolation is used to interpolate the nonsensitive regions and a neural network is proposed to interpolate the sensitive regions along edge directions. ...
In this paper, a novel human visual system (HVS)directed neural-network-based adaptive interpolation scheme for natural image is proposed. ...
The weighted interpolation is used and can be presented as (1) where the weights are derived from a neural network. ...
doi:10.1109/tfuzz.2006.889875
fatcat:teviyqmifzhbxbnhbrduawnnam
Neural-net modeling for direct and inverse problems of shell theory
2016
IOP Conference Series: Materials Science and Engineering
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Some results of neural-net interpolation and extrapolation for direct and inverse problems are discussed. ...
Effectiveness of the use of neural-net technology for the solving of shell theory problems is shown. ...
We consider the examples of solving direct and inverse problems [4] using neural networks. Similarly to the direct problem, we solved the problem of interpolation and extrapolation type. ...
doi:10.1088/1757-899x/155/1/012031
fatcat:fd2tef4evzceze6aicbafrl33e
A Fast and Accurate Wind Speed and Direction Nowcasting Model for Renewable Energy Management Systems
2021
Energies
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The proposed model uses perturbed observations to train the ensemble networks. The trained model is then used to predict the wind speed and direction. ...
Furthermore, the paper presents an exhaustive investigation of the performance of neural network types and several techniques in training, data splitting, and interpolation. ...
Acknowledgment: The authors would like to express their thanks and deep appreciation to the Directorate General of Meteorology, Civil Aviation Authority for providing the meteorological data used in this ...
doi:10.3390/en14237878
fatcat:a47342v4zrecbimuhe4i7evjhi
Content-adaptive neural filters for image interpolation using pixel classification
2005
Applications of Neural Networks and Machine Learning in Image Processing IX
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We propose a new class of non-linear filters for image interpolation, content-adaptive neural filters using pixel classification. ...
In this paper, we propose a new class of non-linear filters for image interpolation, content-adaptive neural (CN) filters using pixel classification, that is, the coefficients of the proposed neural filters ...
CONCLUSION In this paper, we proposed content-adaptive neural filters for image interpolation as a direct extension of the content-adaptive linear filters using the same pixel classification. ...
doi:10.1117/12.592472
fatcat:jd2z6etvpregng25xpxczisryq
Scanned images resolution improvement using neural networks
2007
Neural computing & applications (Print)
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A novel method of improving the spatial resolution of scanned images, by means of neural networks, is presented in this paper. ...
Images of different resolution, originating from scanner, successively train a neural network, which learns to improve resolution from 25 to 50 pixels-per-inch (ppi), then from 100 to 200 ppi and finally ...
A novel image interpolation scheme, using an artificial neural network, is described in [13] . ...
doi:10.1007/s00521-007-0106-x
fatcat:fsebqqyebfheppzzkpt7h54eju
Comparison of Three Compensation Methods for the Touch-trigger Probe Pretravel Errors
2020
IOP Conference Series: Materials Science and Engineering
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Subsequently, the calibration data are used in three compensation methods that the bilinear interpolation method, the bicubic Coons pitch interpolation method and the neural network method. ...
On-machine inspection (OMI) system has been used extensively for automatic setting of the workpiece and determination of kinematic error in machine tool. ...
Third, neural network method is used to calculate the pre-travel errors in un-calibrated directions. ...
doi:10.1088/1757-899x/751/1/012036
fatcat:nio6enfyurfi7all3s467qnmlq
Adaptive Demosaicking using Multiple Neural Networks
2006
Machine Learning for Signal Processing
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And interpolation is edge-directed with different networks for different chosen directions. ...
Based on this, an adaptive scheme is proposed that uses more complex neural networks to tackle steep areas in larger sizes of neighborhoods. ...
This is an advantage to use neural networks. ...
doi:10.1109/mlsp.2006.275574
fatcat:m6fqvfqeundrpiacvzg5i7dxli
Artificial Neural Networks for Single-Image Super-Resolution
2015
International Journal of Computer Applications
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The performance of neural network is compared to bicubic interpolation method in terms of PSNR and MSE. ...
The process is a tradeoff between efficiency, time and the quality of output images obtained .In present paper, a feed forward neural network using supervised training for image upscaling is proposed. ...
The paper implements image upscaling via artificial neural networks using bicubic interpolation. ...
doi:10.5120/21786-5075
fatcat:h524gnmgezazjp4nv3sp5mcjlu
Deep-neural-network based sinogram synthesis for sparse-view CT image reconstruction
2018
IEEE Transactions on Radiation and Plasma Medical Sciences
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In this work, we introduce a deep-neural-network-enabled sinogram synthesis method for sparse-view CT, and show its outperformance to the existing interpolation methods and also to the iterative image ...
Interpolation methods have also been utilized to fill the missing data in the sinogram of sparse-view CT thus providing synthetically full data for analytic image reconstruction. ...
directional interpolation), and images from the sinograms synthesized by two different deep neural networks. ...
doi:10.1109/trpms.2018.2867611
fatcat:7mb5jcn2jfacjlhka7e3pwgiu4
Mobile Position Estimation based on Three Angles of Arrival using an Interpolative Neural Network
2014
International Journal of Computer Applications
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General Terms Neural networks. Keywords Angle of arrival (AOA), average position, optimal position, interpolative neural network. ...
In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. ...
If , it is a heteroassociative neural network, while if , it is an interpolative neural network. ...
doi:10.5120/17534-8109
fatcat:kb2wbzbym5a6vbap6pqec6zcni
Light Source Storage and Interpolation for Global Illumination: A Neural Solution
[chapter]
2009
Studies in Computational Intelligence
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The data describing the luminances distribution are used to train a dedicated neural network during a learning step. ...
In this paper we propose to approximate any photometric solid by the way of artificial neural networks. ...
Neural Networks for Photometric Representation
Structure of the Neural Network For this work, we used a network with three layers. ...
doi:10.1007/978-3-642-03452-7_5
fatcat:7dzc3djq6fe2nn23bsevr2jq44
Video Frame Interpolation via Adaptive Separable Convolution
[article]
2017
arXiv
pre-print
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This deep neural network is trained end-to-end using widely available video data without any human annotation. ...
To address this problem, this paper formulates frame interpolation as local separable convolution over input frames using pairs of 1D kernels. ...
Figures 5 (top) , 6 (top) are used with permission from Gabor Tarnok. ...
arXiv:1708.01692v1
fatcat:5433jh62hfa6ppfn3d5zmeyi4a
Video Frame Interpolation via Adaptive Separable Convolution
2017
2017 IEEE International Conference on Computer Vision (ICCV)
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This deep neural network is trained end-to-end using widely available video data without any human annotation. ...
To address this problem, this paper formulates frame interpolation as local separable convolution over input frames using pairs of 1D kernels. ...
Figures 5 (top) , 6 (top) are used with permission from Gabor Tarnok. ...
doi:10.1109/iccv.2017.37
dblp:conf/iccv/NiklausML17
fatcat:6qa4dnf3cza5xm5swqyyx2n5sm
A Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the Prediction of the Daily Direct Solar Radiation
2018
Energies
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As a result, a hybrid dataset is used as neural network input. ...
For that, a Nonlinear Autoregressive Exogenous (NARX) neural network is used. All the specific conditions of the sailboat operation are taken into account. ...
Figure 14 shows an example of predicted direct solar radiation day using the obtained NARX neural network model. ...
doi:10.3390/en11030620
fatcat:u2lhhywznfbmdn7kmgwciif6s4
Neural BTF Compression and Interpolation
2019
Computer graphics forum (Print)
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In light of these observations, we propose a neural network-based BTF representation inspired by autoencoders: our encoder compresses each texel to a small set of latent coefficients, while our decoder ...
An alternative approach uses analytic model fitting to approximate the BTF data, using continuous functions that naturally interpolate well, but whose expressive range is often not wide enough to faithfully ...
Neural Networks. Several recent works have started using neural networks to render and approximate light transport [RWG * 13, RDL * 15]. Maximov et al. ...
doi:10.1111/cgf.13633
fatcat:jdi53znepfbffanmzgnvbknq6u
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