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作者： Mitianoudis, Nikolaos Papamarkos, Nikolaos Image Processing and Multimedia Laboratory Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi67100 Greece

ISBN: (纸本)9781479957514

In this paper, the authors exploit a multispectral image representation to perform more accurate document image binarisation compared to previous color representations. In the first stage, image fusion is employed to create a 'document' and a 'background' image. In the second stage, the FastICA algorithm is used to perform background subtraction. In the third stage, a spatial kernel K-harmonic means classifier binarizes the FastICA output. The proposed system outperforms previous efforts on document image binarization. © 2014 IEEE.

关键词： Image fusion

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Features for phoneme independent speaker identification

Features for phoneme independent speaker identification

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2012 3rd IEEE/IET International Conference on Audio, Language and Image processing, ICALIP 2012

作者： Wang, Jianglin Ji, An Johnson, Michael T. Speech and Signal Processing Laboratory Department of Electrical and Computer Engineering Marquette University Milwaukee WI United States

ISBN: (纸本)9781467301718

This paper describes a unique cross-phoneme speaker identification experiment, using deliberately mismatched phoneme sets for training and testing. The underlying goal is to identify features that represent broad individually unique characteristics rather than those that represent phonetic differences, as are more typical of modern speaker identification and verification systems. A wide range of features are proposed and evaluated within this context using a Gaussian Mixture Model framework. The results show that log-area ratio has better phonetic independence than MFCCs, that residual phase carries substantial speaker information, and identifies several other features that also have usefulness for speaker identification independent of phonetic content. © 2012 IEEE.

关键词： Gaussian distribution

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Color reduction by using a new self-growing and self-organized neural network

Color reduction by using a new self-growing and self-organiz...

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2nd International Conference on Video, Vision and Graphics, VVG 2005

作者： Atsalakis, A. Papamarkos, N. Image Processing and Multimedia Laboratory Department of Electrical and Computer Engineering Democritus University of Thrace 67100 Xanthi Greece

ISBN: (纸本)9783905673579

A new method for the reduction of the number of colors in a digital image is proposed. The new method is based on the developed of a new neural network classifier that combines the advantages of the Growing Neural Gas (GNG) and the Kohonen Self-Organized Feature Map (SOFM) neural networks. We call the new neural network: Self-Growing and Self-Organized Neural Gas (SGONG). Its main advantage is that it defines the number of the created neurons and their topology in an automatic way. As a consecutive, isolated color classes, which may correspond to significant image details, can be obtained. The SGONG is fed by the color components and additional spatial features. To speed up the entire algorithm and to reduce memory requirements, a fractal scanning sub-sampling technique is used. The method is applicable to any type of color images and it can accommodate any type of color space. © The Eurographics Association 2005.

关键词： Color

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Text extraction using document structure features and support vector machines

Text extraction using document structure features and suppor...

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11th IASTED International Conference on computer Graphics and Imaging, CGIM 2010

作者： Zagoris, Konstantinos Papamarkos, Nikos Image Processing and Multimedia Laboratory Department of Electrical and Computer Engineering Democritus University of Thrace 67100 Xanthi Greece

ISBN: (纸本)9780889868243

In order to successfully locate and retrieve document images such as technical articles and newspapers, a text localization technique must be employed. The proposed method detects and extracts homogeneous text areas in document images indifferent to font types and size by using connected components analysis to detect blocks of foreground objects. Next, a descriptor that consists of a set of structural features is extracted from the merged blocks and used as input to a trained Support Vector Machines (SVM). Finally, the output of the SVM classifies the block as text or not.

关键词： Support vector machines

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Estimation of proper parameter values for document binarization

Estimation of proper parameter values for document binarizat...

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10th IASTED International Conference on computer Graphics and Imaging, CGIM 2008

作者： Badekas, E. Papamarkos, N. Image Processing and Multimedia Laboratory Department of Electrical and Computer Engineering Democritus University of Thrace 67100 Xanthi Greece

ISBN: (纸本)9780889867192

Most of the existing document-binarization techniques deal with many parameters that require a priori setting of their values. Due to the unknown of the ground-truth images, the evaluation of document binarization techniques is subjective and employs human observers for the estimation of the appropriate parameter values. The selection of the appropriate values for these parameters is crucial and influences to the final binarization. However, there is no predetermined set of parameters that guarantees optimal binarization for all document images. This paper proposes a new technique that allows the estimation of proper parameters values for each one of the document binarization techniques. The proposed approach is based on a statistical performance analysis of a set of binarization results, which are obtained by applying various binarization techniques with different parameter values. The proposed statistical performance analysis can also depicts the best document binarization result obtained by a set of document binarization techniques.

关键词： Parameter estimation

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Motion compensated frame interpolation using adaptive adjacency pixel information

Motion compensated frame interpolation using adaptive adjace...

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International Conference on computer Graphics, Imaging and Visualization

作者： Oh, Hyeongchul Lee, Joohyun Min, Changki Jeong, Jechang Image Communication and Signal Processing Laboratory Department of Electrical and Computer Engineering Hanyang University Seoul Korea Republic of

ISBN: (纸本)9780769541662

We propose an adaptive motion compensated frame interpolation scheme which is capable of developing a frame rate from a lower number into a higher number and a decoded video quality at the decoder. The proposed algorithm utilizes the preliminary frames of the forward and backward directions using bilateral prediction. In the processing of the preliminary frames, an additional interpolation is performed to fill the occlusion areas. If the calculated values between the reference and current frames are larger than the predetermined threshold, the block is chosen as the occlusion area. In addition, we performed a re-search in order to acquire the best blocks, taking into account the number of available adjacent blocks for the occlusion areas. The experimental results show that the performance of the proposed algorithm has better PSNR and visual quality than those of the conventional methods. © 2010 IEEE.

关键词： Motion compensation

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Frame interpolation method based on adaptive threshold and adjacent pixels

Frame interpolation method based on adaptive threshold and a...

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6th International Conference on Intelligent Information Hiding and Multimedia Signal processing, IIHMSP 2010

ISBN: (纸本)9780769542225

This paper presents a frame interpolation algorithm using the motion information of some object within the estimated blocks. The proposed algorithm uses two initial frames that are generated based on the backward and forward frames using the motion vectors. In this process, the occlusion regions are occurred in two initial frames since the optimal block is only selected by threshold. Furthermore, the regions are irregularly appeared because of that the selected block is interpolated on half position between the estimated motion vectors. Two initial frames are merged to interpolate the occlusion regions. Also, the occlusion areas, which are still existence in the merged frame, are interpolated by using the neighboring pixel information and the available data in the occlusion block. In this paper, the experimental results show that the performance of the proposed algorithm has better PSNR and the visual quality than the conventional algorithms. © 2010 IEEE.

关键词： Motion compensation

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DEGREES OF CYCLOSTATIONARITY AND THEIR APPLICATION TO SIGNAL-DETECTION AND ESTIMATION

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SIGNAL processing 1991年第3期22卷 287-297页

作者： ZIVANOVIC, GD GARDNER, WA Computer Systems Design Laboratory “Boris Kidrič” Institute Vinča P.O. Box 522 11001 Belgrade Yugoslavia Signal Processing Group Department of Electrical Engineering & Computer Science University of California Davis CA 95616 USA

The problem of defining an appropriate measure of the degree of nonstationarity for stochastic processes that exhibit cyclostationarity is addressed. After discussing several candidate measures of degree of nonstationarity, one particularly promising measure is adopted. By decomposing this measure, several component measures are arrived at. Bounds on these measures are derived and their utility in applications involving signal detection and estimation is established. Examples are presented to illustrate the calculation of degrees of nonstationarity for several types of cyclostationary signals.

关键词： CYCLOSTATIONARY PROCESS DEGREE OF CYCLOSTATIONARITY INSTANTANEOUS SPECTRUM SPECTRAL CORRELATION

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Transfer learning approach to modeling multichannel gate-all-around nanosheet field-effect transistors under work function fluctuations

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engineering Applications of Artificial Intelligence 2025年 148卷

作者： Dash, Sagarika Li, Yiming Parallel and Scientific Computing Laboratory National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Electrical Engineering and Computer Science International Graduate Program National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Institute of Communications Engineering National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Institute of Biomedical Engineering National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Institute of Artificial Intelligence Innovation National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Department of Electronics and Electrical Engineering National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan Department of Microelectronics National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300093 Taiwan

Deep learning (DL) has significantly advanced various industries, including semiconductors, by providing sophisticated methods for analyzing emerging device data. Transfer learning (TL), a prominent DL topology, leverages knowledge from a pre-trained model to improve the performance of a specific target task. This study aims to apply TL to predict the impact of work function fluctuation (WKF) on the variability of threshold voltage (σVTH) in gate-all-around silicon nanosheet field-effect transistors (GAA Si NS FETs). We used TL to transfer knowledge from models trained on 1-channel (1ch) GAA Si NS FETs to more complex 4-channel (4ch) counterparts. The prediction accuracy is evaluated by using the mean square error(MSE), root mean square error (RMSE), and the mean absolute error(MAE) metrics. Our TL approach achieved an error rate of less than 1%, demonstrating high accuracy in predicting WKF effects on σ VTH of 4ch GAA Si NS FETs using only 500 samples. This study presents a pioneering application of TL using a one-dimensional (1D) convolutional neural network (CNN) long short-term memory (LSTM) topology in semiconductor device technology. The results effectively address the challenge of predicting σ VTH variations in advanced GAA Si NS FETs because of WKF, which eliminates the need for extensive semiconductor device simulations. © 2025 Elsevier Ltd

关键词： Convolutional neural networks

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A Journey from signal processing to surveillance

A Journey from signal processing to surveillance

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2007 IEEE Conference on Advanced Video and Signal Based Surveillance, AVSS 2007

作者： Chen, Tsuhan Advanced Multimedia Processing Laboratory Dept. of Electrical Computer Engineering Carnegie Mellon University Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA United States IEEE Signal Processing Society

ISBN: (纸本)9781424416967

Traditionally, signal processing is considered simply lowlevel processing. In the past decade, however, signal processing has grown to become the area where a variety of tools are created to solve high-level problems that conventionally would be studied by computer vision or machine learning researchers exclusively. For example, multiresolution analysis created popular image features like SIFT (scale-invariant feature transform), and statistical analysis gave birth to graphical models such as HMM (hidden Markov models) and topic models. In this talk, we will use one application to illustrate this growth of signal processing: object discovery, i.e., extracting the "object of interest" from a set of images in a completely unsupervised manner. Often based on image features like SIFT, and the topic models, object discovery has recently attracted a lot of attention in video content extraction. In this talk, we will outline this approach and extend it from still images to motion videos. We will propose a novel spatial-temporal framework that applies statistical models to both appearance modeling and motion modeling. The spatial and temporal models are integrated so that motion ambiguities can be resolved by appearance, and appearance ambiguities can be resolved by motion. In addition, we can extract hierarchical relationships among objects, completely driven by data without any manual labeling. This framework finds application in video retrieval (e.g., for YouTube or Google Video) and video surveillance. © 2007 IEEE.

关键词： Hidden Markov models

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