Quantum Computing Approaches for Vector Quantization—Current Perspectives and Developments [PDF]
Entropy, 2023 In the field of machine learning, vector quantization is a category of low-complexity approaches that are nonetheless powerful for data representation and clustering or classification tasks. Vector quantization is based on the idea of representing a data
Alexander Engelsberger, Thomas Villmann
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Spherical-Cap Approximation of Vector Quantization for Quantization-Based Combining in MIMO Broadcast Channels with Limited Feedback [PDF]
Sensors, 2022 The spherical-cap approximation of vector quantization (SCVQ) is an analytical model used for the mathematical analysis of multiple-input multiple-output (MIMO) systems with limited feedback.
Moonsik Min, Tae-Kyoung Kim
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Steganography based on Vector Quantization Technique [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2013 The present research was aimed to implement a new Steganographic algorithm for Images in Vector Quantization (VQ) compressed domain, since the compressed image considers a secure cover for data to be embedded to avoid attention of unauthorized persons ...
Ansam Osamah, Ahmed Nori
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Accelerating Families of Fuzzy K-Means Algorithms for Vector Quantization Codebook Design [PDF]
Sensors, 2016 The performance of signal processing systems based on vector quantization depends on codebook design. In the image compression scenario, the quality of the reconstructed images depends on the codebooks used.
Edson Mata +4 more
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MECO: Mixture-of-Expert Codebooks for Multiple Dense Prediction Tasks [PDF]
SensorsAutonomous systems operating in embedded environments require robust scene understanding under computational constraints. Multi-task learning offers a compact alternative to deploying multiple task-specific models by jointly solving dense prediction ...
Gyutae Hwang, Sang Jun Lee
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NSVQ: Noise Substitution in Vector Quantization for Machine Learning
IEEE Access, 2022 Machine learning algorithms have been shown to be highly effective in solving optimization problems in a wide range of applications. Such algorithms typically use gradient descent with backpropagation and the chain rule.
Mohammad Hassan Vali, Tom Backstrom
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Research on Quantization Parameter Decision Scheme for High Efficiency Video Coding
Applied Sciences, 2023 High-Efficiency Video Coding (HEVC) is one of the most widely studied coding standards. It still uses the block-based hybrid coding framework of Advanced Video Coding (AVC), and compared to AVC, it can double the compression ratio while maintaining the ...
Xuesong Jin, Yansong Chai
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New Method to Reduce the Size of Codebook in Vector Quantization of Images [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2005 The vector quantization method for image compression inherently requires the generation of a codebook which has to be made available for both the encoding and decoding processes.
Sahar Ahmed
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Multiple-Description Multistage Vector Quantization
EURASIP Journal on Audio, Speech, and Music Processing, 2007 Multistage vector quantization (MSVQ) is a technique for low complexity implementation of high-dimensional quantizers, which has found applications within speech, audio, and image coding.
Pradeepa Yahampath
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IEEE Photonics Journal, 2019 In this paper, a two-dimensional (2-D) vector quantization with vector linear prediction (VLP-VQ) is proposed to improve the transmission performance of the digital mobile fronthaul (MFH).
Jia Ye +5 more
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