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Image registration and image interpolation in volume rendering of cross sections
(1995-12-01)
We outline a method for registration of images of cross sections using the concepts of The Generalized Hough Transform (GHT). The approach may be useful in situations where automation should be a concern. To overcome known ...
Radon transform-based microseismic event detection and signal-to-noise ratio enhancement
(Elsevier Science, 2015-02)
We present an adaptive filtering method to denoise downhole microseismic data. The methodology uses the apex-shifted parabolic Radon transform. The algorithm is implemented in two steps. In the first step we apply the ...
QAM-DWT-SVD Based Watermarking Scheme for Medical Images
This paper presents a new semi-blind image watermarking system for medical applications. The new scheme utilizes Singular Value Decomposition (SVD) and Discrete Wavelet Transform (DWT) to embed a textual data into original ...
ISER: selection of differentially expressed genes from DNA array data by non-linear data transformations and local fitting
(Oxford Univ PressOxfordInglaterra, 2005)
Unidade de condicionamento de sinais como elemento de interface entre transformadores de instrumentação e dispositivo de aquisição de dados
(Universidade Federal de Santa MariaBrasilUFSMCentro de Tecnologia, 2019-01-14)
This work describes the development of a voltage and current signal conditioning unit, applied as interface element between potential and current transformers, used in transformers tests, and a data acquisition device. ...
Compensated convexity on bounded domains, mixed Moreau envelopes and computational methods
(Elsevier Science Inc., 2021-06)
Compensated convex transforms have been introduced for extended real valued functions defined over Rn. In their application to image processing, interpolation and shape interrogation, where one deals with functions defined ...
A novel neural model to electrical load forecasting in transformers
(Int Inst Informatics & Systemics, 2001-01-01)
The paper describes a novel neural model to electrical load forecasting in transformers. The network acts as identifier of structural features to forecast process. So that output parameters can be estimated and generalized ...
A novel neural model to electrical load forecasting in transformers
(Int Inst Informatics & Systemics, 2001-01-01)
The paper describes a novel neural model to electrical load forecasting in transformers. The network acts as identifier of structural features to forecast process. So that output parameters can be estimated and generalized ...