vector quantization (122 Ergebnisse)

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The Annals of Applied Probability, 1997, Vol. 7, No. 3, 32 pages agrafées de 17x25 cm Bon état.

Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 144 | Sprache: Englisch | Produktart: Bücher.

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Broschiert; Zustand: Gut. VI, 109, 32 S. : Ill., graph. Darst. ; 21 cm Das hier angebotene Buch befindet sich in einem ordentlichen Zustand. Sprache: Deutsch Gewicht in Gramm: 230.

Taschenbuch. Zustand: Neu. Neuware -Speaker Recognition is one of the most useful biometric recognition techniques in this world where insecurity is a major concern. This book introduces a method for speaker recognition on the basis of the individual information included in speech waves. This can mainly be divided into two parts speaker identification and speaker verification. Speaker Identification find outs which speaker has uttered the given speech and Speaker Verification verifies their identity. Speaker recognition technology is the most potential technology to create new services that will make our everyday lives more secured.Books on Demand GmbH, Überseering 33, 22297 Hamburg 52 pp. Englisch.

Taschenbuch. Zustand: Neu. Neuware -This book presents a novel approach for Face Recognition using ¿Vector Quantization¿. Face Recognition is one of the popular biometric techniques used in today¿s era. A face recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. Vector quantization is simple image compression technique. It is efficient for image coding because it reduces computational complexity. VQ compression is highly asymmetric in processing time: choosing an optimal codebook takes huge amounts of calculations, but decompression is lightning-fast¿only one table lookup per vector. This makes VQ an excellent choice for face recognition. In this book four different VQ algorithms namely LBG, KPE, KMCG and KFCG are used to observe the efficiency of face recognition system. Efficiency is calculated in terms of recognition rate and computational complexity. It has been observed that KPE, KMCG and KFCG outperform LBG which is known as benchmark in vector quantization. Proposed techniques are compared with traditional DCT and Walsh transform also. It proves better than transform techniques.Books on Demand GmbH, Überseering 33, 22297 Hamburg 96 pp. Englisch.

Taschenbuch. Zustand: Neu. Neuware -Automatic Speech Recognition (ASR) has progressed considerably over the past several decades, but still has not achieved the potential imagined at its very beginning. Almost all of the existing applications of ASR systems are PC based. This work is an attempt to develop a speech recognition system that is independent of any PC support and is small enough in size to be used in a daily use consumer appliance. The proposed system would recognize isolated word utterances from a limited vocabulary, provide speaker independence, require less memory and be cost-efficient compared to present ASR systems. In this system, isolated word recognition is performed by using Vector Quantization (VQ) and Mel-Frequency Cepstral Coefficient (MFCC). The final system has been implemented on a vero board with an ATMEGA32 microcontroller. Learning and recognition algorithm have been used to recognize the speech utterances.Books on Demand GmbH, Überseering 33, 22297 Hamburg 80 pp. Englisch.

Taschenbuch. Zustand: Neu. Neuware -The rapid growth and development of electronic imaging in the recent years has led to large scale digital media archives. These are increasingly becoming popular as more and more digital media contents are created and deployed online every day. A critical issue in designing such archives is effective storage of the data. Uncompressed data requires more storage and huge bandwidth for transmission. Though the cost of storage is rapidly dropping, compression still remains as a challenging issue due to the growing number of multimedia based online applications. This necessitates the design of highly efficient image compression systems which promise good image quality and compression ratios with low computational complexity. This book is an outcome of the research in vector quantization based methods for compressing still images. It discusses novel image compression methods with performance analysis using standard compression metrics and their vital role in real-time applications. The proposed methods can be used in applications like Medical Image Processing, Mobile Applications, Biometrics, Remote Sensing and other online web applications.Books on Demand GmbH, Überseering 33, 22297 Hamburg 188 pp. Englisch.

Zustand: Gut. Zustand: Gut | Seiten: 170 | Sprache: Englisch | Produktart: Bücher.

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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Different methods for compression were suggested and investigated; these methods exploit the space segmentation, frequency transform, and quantization features. Various transforms schemes were test to involve different methods combinations. Image coding algorithms based on coupling frequency domain with spatial domain has attracted wide attention because its good performance appears to confirm the promised efficiencies of hierarchical representation. Space segmentation is an important step in analyze the interested reign. This step works as a feature classification to determine the way to derive with each segmented region. The region is a variable size block, which step over the disadvantages of fixed size blocks by using the Quadtree partitioning. Wavelet Transform provides a framework of variety of research areas. In this book the architecture of Lifting Scheme was implemented by adopting the Wavelet filters 9/7tap and 5/3tap. Vector Quantization is a well-known technique among the blocks based compression techniques. Several modifications have been proposed, implemented and tested, the results indicated that the performance of the suggested system is well acceptable.

Taschenbuch. Zustand: Neu. Neuware -In this collection, the reader can ¿nd recent advancements in self-organizing maps (SOMs) and learning vector quantization (LVQ), including progressive ideas on exploiting features of parallel computing. The collection is balanced in presenting novel theoretical contributions with applied results in traditional ¿elds of SOMs, such as visualization problems and data analysis. Besides, the collection further includes less traditional deployments in trajectory clustering and recent results on exploiting quantum computation. The presented book is worth interest to data analysis and machine learning researchers and practitioners, speci¿cally those interested in being updated with current developments in unsupervised learning, data visualization, and self-organization.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 132 pp. Englisch.

Taschenbuch. Zustand: Neu. Neuware -This book gathers papers presented at the 13th International Workshop on Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization (WSOM+), which was held in Barcelona, Spain, from the 26th to the 28th of June 2019. Since being founded in 1997, the conference has showcased the state of the art in unsupervised machine learning methods related to the successful and widely used self-organizing map (SOM) method, and extending its scope to clustering and data visualization. In this installment of the AISC series, the reader will find theoretical research on SOM, LVQ and related methods, as well as numerous applications to problems in fields ranging from business and engineering to the life sciences. Given the scope of its coverage, the book will be of interest to machine learning researchers and practitioners in general and, more specifically, to those looking for the latest developments in unsupervised learning and data visualization.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 356 pp. Englisch.

Taschenbuch. Zustand: Neu. Neuware -This book contains the articles from the international conference 11th Workshop on Self-Organizing Maps 2016 (WSOM 2016), held at Rice University in Houston, Texas, 6-8 January 2016. WSOM is a biennial international conference series starting with WSOM'97 in Helsinki, Finland, under the guidance and direction of Professor Tuevo Kohonen (Emeritus Professor, Academy of Finland). WSOM brings together the state-of-the-art theory and applications in Competitive Learning Neural Networks: SOMs, LVQs and related paradigms of unsupervised and supervised vector quantization.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 384 pp. Englisch.

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Taschenbuch. Zustand: Neu. Neuware -The book presents the peer-reviewed contributions of the 15th International Workshop on Self-Organizing Maps, Learning Vector Quantization and Beyond (WSOM$+$ 2024), held at the University of Applied Sciences Mittweida (UAS Mitt-weida), Germany, on July 10¿12, 2024.The book highlights new developments in the field of interpretable and explainable machine learning for classification tasks, data compression and visualization. Thereby, the main focus is on prototype-based methods with inherent interpretability, computational sparseness and robustness making them as favorite methods for advanced machine learning tasks in a wide variety of applications ranging from biomedicine, space science, engineering to economics and social sciences, for example. The flexibility and simplicity of those approaches also allow the integration of modern aspects such as deep architectures, probabilistic methods and reasoning as well as relevance learning. The book reflects both new theoretical aspects in this research area and interesting application cases.Thus, this book is recommended for researchers and practitioners in data analytics and machine learning, especially those who are interested in the latest developments in interpretable and robust unsupervised learning, data visualization, classification and self-organization.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 244 pp. Englisch.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The book collects the scientific contributions presented at the 10th Workshop on Self-Organizing Maps (WSOM 2014) held at the University of Applied Sciences Mittweida, Mittweida (Germany, Saxony), on July 2-4, 2014. Starting with the first WSOM-workshop 1997 in Helsinki this workshop focuses on newest results in the field of supervised and unsupervised vector quantization like self-organizing maps for data mining and data classification.This 10th WSOM brought together more than 50 researchers, experts and practitioners in the beautiful small town Mittweida in Saxony (Germany) nearby the mountains Erzgebirge to discuss new developments in the field of unsupervised self-organizing vector quantization systems and learning vector quantization approaches for classification. The book contains the accepted papers of the workshop after a careful review process as well as summaries of the invited talks. Among these book chapters there are excellent examples of the use of self-organizing maps in agriculture, computer science, data visualization, health systems, economics, engineering, social sciences, text and image analysis and time series analysis. Other chapters present the latest theoretical work on self-organizing maps as well as learning vector quantization methods, such as relating those methods to classical statistical decision methods.All the contribution demonstrate that vector quantization methods cover a large range of application areas including data visualization of high-dimensional complex data, advanced decision making and classification or data clustering and data compression.

paperback. Zustand: New. Language:Chinese.Pages Number: 188 Publisher: Science Press Pub. Date :2009-09. This book is a vector quantization technique and its application in image signal processing monographs. The book is divided into eight chapters. detailing the development and application of vector quantization techniques. These include: the basic principles of vector quantization. vector quantization of the development status of the theory of vector quantization. vector quantization codebook formation algorithm. t.

paperback. Zustand: New. Language:Chinese.Pages Number: 306 Publisher: Science Pub. Date :2011-07-01 version 1. Vector quantization in multimedia signal processing applications (author Luzhe Ming. Zheng Weimin. SUN Sheng) is the vector quantization theory and application of monographs. The book first introduces the basic principles of vector quantization and application status. and then introduce the structure of vector quantization and basic ideas. and then describes the basic vector quantization of the three key te.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book is an attempt to unravel the problem of human face recognition. Face recognition is a biometric authentication method that has become more and more relevant in the recent years for the purpose of surveillance. Face recognition is a popular research area where there are different approaches studied in the literature. In this book face recognition problem is handled by applying Principal Component Analysis (PCA), Various Orthogonal transforms and different Vector Quantization (VQ) codebook generation techniques. The Eigen face method tries to find a lower dimensional space for the representation of the face images. The main drawback of PCA is scalability. As dataset changes the whole eigenspace distribution also changes. To avoid this difficulty various orthogonal transforms like DCT, DST, WHT, Slant, Wavelet Transform and newly proposed Kekre's Transform are applied on database. The concept of image energy compaction in low frequency coefficients is explored here.The VQ is considered to be a good data compression method. The key to VQ is the good codebook generation. Here the new technique for codebook generation is introduced as Kekre's Fast Code Book Generation (KFCG).