Download or read book Image Compression with Classified Vector Quantization Using Adaptive Hierarchical Segmentation and Variable Size Codebooks written by Mitesh N. Mehta and published by . This book was released on 1996 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Image Compression Using Adaptive Vector Quantization with Codebook Size Expanded Mechanism written by and published by . This book was released on 1999 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Efficient Codebooks for Vector Quantization Image Compression with an Adaptive Tree Search Algorithm written by Vijay Simha Sitaram and published by . This book was released on 1992 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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Download or read book Image Compression and Classification Using Vector Quantization written by Karen Louise Oehler and published by . This book was released on 1993 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Still Image Data Compression Using Hierarchical Adaptive Dimension Zero tree Residual Vector Quantization written by Dazhong (Chris) Zhang and published by . This book was released on 2005 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Vector Quantization written by Hüseyin Abut and published by Institute of Electrical & Electronics Engineers(IEEE). This book was released on 1990 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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Download or read book Toward Category Level Object Recognition written by Jean Ponce and published by Springer. This book was released on 2007-01-25 with total page 622 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a post-event proceedings volume and contains selected papers based on presentations given, and vivid discussions held, during two workshops held in Taormina in 2003 and 2004. The 30 thoroughly revised papers presented are organized in the following topical sections: recognition of specific objects, recognition of object categories, recognition of object categories with geometric relations, and joint recognition and segmentation.

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Download or read book Fractal Image Compression written by Yuval Fisher and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: One half of the book is authored by Yuval Fisher himself, while articles from another 12 experts in the field present material from different points of view. The focus here is solely on fractal image encoding, with the aim of providing a working code that is usable in applications, while containing the complete details of how to encode and decode images. An indispensable "how to" guide, combining the very latest results in the field. Of interest to a very wide audience, ranging from experts in image processing to high school students.

Download or read book Machine Learning for Audio Image and Video Analysis written by Francesco Camastra and published by Springer. This book was released on 2015-07-21 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition focuses on audio, image and video data, the three main types of input that machines deal with when interacting with the real world. A set of appendices provides the reader with self-contained introductions to the mathematical background necessary to read the book. Divided into three main parts, From Perception to Computation introduces methodologies aimed at representing the data in forms suitable for computer processing, especially when it comes to audio and images. Whilst the second part, Machine Learning includes an extensive overview of statistical techniques aimed at addressing three main problems, namely classification (automatically assigning a data sample to one of the classes belonging to a predefined set), clustering (automatically grouping data samples according to the similarity of their properties) and sequence analysis (automatically mapping a sequence of observations into a sequence of human-understandable symbols). The third part Applications shows how the abstract problems defined in the second part underlie technologies capable to perform complex tasks such as the recognition of hand gestures or the transcription of handwritten data. Machine Learning for Audio, Image and Video Analysis is suitable for students to acquire a solid background in machine learning as well as for practitioners to deepen their knowledge of the state-of-the-art. All application chapters are based on publicly available data and free software packages, thus allowing readers to replicate the experiments.

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