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Jeng-Shyang Pan

Bio: Jeng-Shyang Pan is an academic researcher from Shandong University of Science and Technology. The author has contributed to research in topics: Digital watermarking & Watermark. The author has an hindex of 50, co-authored 789 publications receiving 11645 citations. Previous affiliations of Jeng-Shyang Pan include National Kaohsiung Normal University & Technical University of Ostrava.


Papers
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Book ChapterDOI
03 Jun 2007
TL;DR: The experimental results suggest that the proposed common subfaces approach provides a better representation of individual common feature and achieves a higher recognition rate in the face recognition from a single image per person compared with the traditional methods.
Abstract: In this paper, we propose a face recognition method from a single image per person, called the common subfaces, to solve the "one sample per person" problem. Firstly the single image per person is divided into multiple sub-images, which are regarded as the training samples for feature extraction. Then we propose a novel formulation of common vector analysis from the space isomorphic mapping view for feature extraction. In the procedure of recognition, the common vector of the subfaces from the test face image is derived with the similar procedure to the common vector, which is then compared with the common vector of each class to predict the class label of query face. The experimental results suggest that the proposed common subfaces approach provides a better representation of individual common feature and achieves a higher recognition rate in the face recognition from a single image per person compared with the traditional methods.

22 citations

Proceedings ArticleDOI
13 Dec 2010
TL;DR: A communication strategy for the parallelized Artificial Bee Colony (ABC) optimization is proposed for solving numerical optimization problems and increases the accuracy of the ABC on finding the near best solution.
Abstract: In this paper, a communication strategy for the parallelized Artificial Bee Colony (ABC) optimization is proposed for solving numerical optimization problems. The artificial agents are split into several independent subpopulations based on the original structure of the ABC, and the proposed communication strategy provides the information flow for the agents to communicate in different subpopulations. Three benchmark functions are used to test the behavior of convergence, the accuracy, and the speed of the proposed method. According to the experimental result, the proposed communicational strategy increases the accuracy of the ABC on finding the near best solution.

22 citations

Proceedings ArticleDOI
25 Aug 2012
TL;DR: A new approach is proposed for hand gesture recognition, that is accomplished by dominant points based hand finger counting under skin color extraction, and the hand gesture contour can be extracted by this mean.
Abstract: In this paper, a new approach is proposed for hand gesture recognition, that is accomplished by dominant points based hand finger counting under skin color extraction. Skin color detection is used as a preprocessing segmentation, and the hand gesture contour can be extracted by this mean. after hand segmentation is done, dominant points based algorithm is used for counting hand fingers in this hand gesture control system. the performance and comparison is evaluated in the end as well. then the hand gesture control system can be implement by fuzzy logical efficiently this way.

22 citations

Book
08 Sep 2013
TL;DR: This book discusses the advanced kernel learning algorithms and its application on face recognition and focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition.
Abstract: Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its newest applications.

22 citations

01 Jan 2020
TL;DR: An improved fish migration optimization (FMO), which adopts novel update equations of individuals and energy and a chieftain concept is introduced and it can attract individuals to exploitation around it.
Abstract: This paper presents an improved fish migration optimization (FMO), which adopts novel update equations of individuals and energy. A chieftain concept is introduced and it can attract individuals to exploitation around it. Therefore, the novel algorithm reduced the randomness and improved the convergence ability of the original algorithm. A more flexible update equation of energy is introduced which adjusts the amplitude of energy increase of individuals according to its fitness quality. The performance of the new algorithm is verified by CEC 2013 benchmark function. Besides, the novel algorithm is applied in solving the localization problem of Wireless Sensor Network (WSN) on 3-D terrain.

22 citations


Cited by
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Journal ArticleDOI
TL;DR: It is proved the convergence of a recursive mean shift procedure to the nearest stationary point of the underlying density function and, thus, its utility in detecting the modes of the density.
Abstract: A general non-parametric technique is proposed for the analysis of a complex multimodal feature space and to delineate arbitrarily shaped clusters in it. The basic computational module of the technique is an old pattern recognition procedure: the mean shift. For discrete data, we prove the convergence of a recursive mean shift procedure to the nearest stationary point of the underlying density function and, thus, its utility in detecting the modes of the density. The relation of the mean shift procedure to the Nadaraya-Watson estimator from kernel regression and the robust M-estimators; of location is also established. Algorithms for two low-level vision tasks discontinuity-preserving smoothing and image segmentation - are described as applications. In these algorithms, the only user-set parameter is the resolution of the analysis, and either gray-level or color images are accepted as input. Extensive experimental results illustrate their excellent performance.

11,727 citations

Book
24 Oct 2001
TL;DR: Digital Watermarking covers the crucial research findings in the field and explains the principles underlying digital watermarking technologies, describes the requirements that have given rise to them, and discusses the diverse ends to which these technologies are being applied.
Abstract: Digital watermarking is a key ingredient to copyright protection. It provides a solution to illegal copying of digital material and has many other useful applications such as broadcast monitoring and the recording of electronic transactions. Now, for the first time, there is a book that focuses exclusively on this exciting technology. Digital Watermarking covers the crucial research findings in the field: it explains the principles underlying digital watermarking technologies, describes the requirements that have given rise to them, and discusses the diverse ends to which these technologies are being applied. As a result, additional groundwork is laid for future developments in this field, helping the reader understand and anticipate new approaches and applications.

2,849 citations

Proceedings Article
01 Jan 1999

2,010 citations

Posted Content
TL;DR: This paper defines and explores proofs of retrievability (PORs), a POR scheme that enables an archive or back-up service to produce a concise proof that a user can retrieve a target file F, that is, that the archive retains and reliably transmits file data sufficient for the user to recover F in its entirety.
Abstract: In this paper, we define and explore proofs of retrievability (PORs). A POR scheme enables an archive or back-up service (prover) to produce a concise proof that a user (verifier) can retrieve a target file F, that is, that the archive retains and reliably transmits file data sufficient for the user to recover F in its entirety.A POR may be viewed as a kind of cryptographic proof of knowledge (POK), but one specially designed to handle a large file (or bitstring) F. We explore POR protocols here in which the communication costs, number of memory accesses for the prover, and storage requirements of the user (verifier) are small parameters essentially independent of the length of F. In addition to proposing new, practical POR constructions, we explore implementation considerations and optimizations that bear on previously explored, related schemes.In a POR, unlike a POK, neither the prover nor the verifier need actually have knowledge of F. PORs give rise to a new and unusual security definition whose formulation is another contribution of our work.We view PORs as an important tool for semi-trusted online archives. Existing cryptographic techniques help users ensure the privacy and integrity of files they retrieve. It is also natural, however, for users to want to verify that archives do not delete or modify files prior to retrieval. The goal of a POR is to accomplish these checks without users having to download the files themselves. A POR can also provide quality-of-service guarantees, i.e., show that a file is retrievable within a certain time bound.

1,783 citations