Author: Nuno Miguel Borges de Pinho Cruz de VasconcelosPublisher:
ISBN:
Category :
Languages : en
Pages : 254
Book Description
Library-based Image Coding Using Vector Quantization of the Prediction Space
Author: Nuno Miguel Borges de Pinho Cruz de VasconcelosPublisher:
ISBN:
Category :
Languages : en
Pages : 254
Book Description
Masters Theses in the Pure and Applied Sciences
Author: Wade H. ShaferPublisher: Springer Science & Business Media
ISBN: 1461519691
Category : Science
Languages : en
Pages : 426
Book Description
Masters Theses in the Pure and Applied Sciences was first conceived, published, and disseminated by the Center for Information and Numerical Data Analysis and Synthesis (CINDAS)* at Purdue University in 1957, starting its coverage of theses with the academic year 1955. Beginning with Volume 13, the printing and dis semination phases of the activity were transferred to University Microfilms/Xerox of Ann Arbor, Michigan, with the thought that such an arrangement would be more beneficial to the academic and general scientific and technical community. After five years of this joint undertaking we had concluded that it was in the interest of all concerned if the printing and distribution of the volumes were handled by an international publishing house to assure improved service and broader dissemination. Hence, starting with Volume 18, Masters Theses in the Pure and Applied Sciences has been disseminated on a worldwide basis by Plenum Publishing Corporation of New York, and in the same year the coverage was broadened to include Canadian universities. All back issues can also be ordered from Plenum. We have reported in Volume 38 (thesis year 1993) a total of 13,787 thesis titles from 22 Canadian and 164 United States universities. We are sure that this broader base for these titles reported will greatly enhance the value of this impor tant annual reference work. While Volume 38 reports theses submitted in 1993, on occasion, certain uni versities do report theses submitted in previous years but not reported at the time.
Algorithms and Architectures for Image Coding Using Vector Quantization
Author: S. PanchanathanPublisher:
ISBN:
Category : Coding theory
Languages : en
Pages : 0
Book Description
High-compression Image Coding Using Predictive Residual Vector Quantization
Author: Syed A. RizviAlgorithms and Architectures for Image Coding Using Vector Quantization
Author: S. PanchanathanPublisher:
ISBN:
Category : Coding theory
Languages : en
Pages : 294
Book Description
Exploring Vector Quantization with Vision Transformer for Image Classification Problem
Author: Publisher:
ISBN:
Category : Computer vision
Languages : en
Pages : 0
Book Description
Transformer model is a cutting-edge machine learning model which utilizes the self-attention mechanism that showed significant improvement on performance, first, in the field of Natural Language Processing, then reapplied in computer vision as Vision Transformer (ViT). Vector Quantization is a traditional technique for lossy compression to reduce the data size while attempting to retain most of the significant information. It achieves this by dividing the data into patches and creating the approximation representation using a codebook. This thesis aims to bring well established vector quantization techniques and cutting-edge vision transformer models together and explore the performance, trade-off, and challenges of combining the technology for image classification purposes. The work first explores the vector quantization in two different ways, color space and image space, encoding using the Generalized Lloyd algorithm. The quantized data is fed into ViT model instead of original images. Next, the work examines the various structures of ViT along with training techniques identify how to effectively train the model using quantified image data. Finally, performance is evaluated among base, color quantized, and image quantized data from scratch as well as a pre-trained model. The result shows that quantization in both color space and image space produces comparable performance. This happens when the input image is provided in a decoded format. We also observe that comparable performance is achieved even if the input image size is reduced to one tenth of the original image size. This indicates that the original image contains much more detail than necessary to perform the classification. The result also shows that the quantization of image space, when provided as an encoded image, reduces the performance compared to base case. This happens due to the lack of context, leading to the misclassification of similarly shaped objects. The framework and proces provided in this thesis could be used as a base to further accelerate the exploration of the use of vector quantization in image classification tasks.
Low Rate Image Coding Using Vector Quantization
Author: Anamitra MakurPublisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages : 226
Book Description
Masters Theses in the Pure and Applied Sciences
Author: Sade H ShaferPublisher: Springer Science & Business Media
ISBN:
Category : Education
Languages : en
Pages : 440
Book Description
Cited in Sheehy, Chen, and Hurt . Volume 38 (thesis year 1993) reports a total of 13,787 thesis titles from 22 Canadian and 164 US universities. As in previous volumes, thesis titles are arranged by discipline and by university within each discipline. Any accredited university or college with a grad
Image Coding Based on Address Vector Quantization
Author: Yushu FengPublisher:
ISBN:
Category : Image processing
Languages : en
Pages : 348
Book Description
Optimal Signal Processing for Vector Quantization Based Image and Video Coding
Author: Shipeng LiPublisher:
ISBN:
Category : Data compression (Telecommunication)
Languages : en
Pages : 350
Book Description