Results 51 to 60 of about 21,396 (309)

Reference-Vector Removed Product Quantization for Approximate Nearest Neighbor Search

Applied Sciences
This paper proposes a decorrelation scheme based on product quantization, termed Reference-Vector Removed Product Quantization (RvRPQ), for approximate nearest neighbor (ANN) search.
Yang Wang, Ce Xu, Xueyi Wu
doaj   +1 more source

Self‐Powered Bearing Sensing and Real‐Time Fault Diagnosis Enabled by Non‐Invasive Triboelectric Sensors and Edge AI Acceleration

Advanced Science, EarlyView.
This study achieves the synergistic integration of self‐powered sensing and edge AI acceleration to establish a real‐time fault diagnosis system. The proposed TENG‐based self‐powered bearing sensor (NSE‐TBS) and FPGA‐accelerated edge AI framework fundamentally break through the inherent limitations of conventional monitoring systems, including complex ...
Kehui Zhu, Zhongheng Liu, Xinming Li, Jinrui Zhang, Meng Li, Yiming Guo, Lihua Han, Yanxue Wang   +7 more
wiley   +1 more source

Improving learning vector quantization using data reduction

IJAIN (International Journal of Advances in Intelligent Informatics), 2019
Learning Vector Quantization (LVQ) is a supervised learning algorithm commonly used for statistical classification and pattern recognition. The competitive layer in LVQ studies the input vectors and classifies them into the correct classes. The amount of
Pande Nyoman Ariyuda Semadi, Reza Pulungan   +1 more
doaj   +1 more source

Wavelet-based fragile watermarking scheme for image authentication [PDF]

, 2007
We propose a fragile watermarking scheme in the wavelet transform domain that is sensitive to all kinds of manipulations and has the ability to localize the tampered regions.
Si, Huayin, Li, Chang-Tsun
core   +1 more source

Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors

Advanced Science, EarlyView.
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung, Gwang Ya Kim, Sejin Kim, Hyunjong Seo, Se Gi Lee, Sang Min Won, Dongjoon Rhee, Joohoon Kang   +7 more
wiley   +1 more source

Handwriting Character Recognition using Vector Quantization Technique

Knowledge Engineering and Data Science, 2019
This paper seeks to explore Learning Vector Quantization (LVQ) processing stage to recognize The Buginese Lontara script from Makassar as well as explaining its accuracy. The testing results of LVQ obtained an accuracy degree of 66.66 %. The most optimal
Haviluddin Haviluddin, Rayner Alfred, Ni’mah Moham, Herman Santoso Pakpahan, Islamiyah Islamiyah, Hario Jati Setyadi   +5 more
doaj   +1 more source

Local feature weighting in nearest prototype classification [PDF]

, 2008
The distance metric is the corner stone of nearest neighbor (NN)-based methods, and therefore, of nearest prototype (NP) algorithms. That is because they classify depending on the similarity of the data.
Isasi, Pedro, Fernández, Fernando, Isasi Viñuela, Pedro   +2 more
core   +1 more source

Full‐Stack Architectures for Intelligent Brain‐Computer Interfaces

Advanced Science, EarlyView.
System‐level overview of brain–computer interfaces (BCIs), illustrating the integration of neural signal acquisition, wireless transmission, and adaptive decoding. Advanced electrode, tissue interfaces, energy‐efficient communication, and robust algorithms collectively enable stable signal quality, real‐time processing, and closed‐loop operation ...
Hee Kyu Lee, Hyun Bin Kim, Sang Uk Park, Janghoon Joo, Jinhong Min, Geumbee Lee, Joohoon Kang, Hyoyoung Jeong, Jae‐Young Yoo, Sang Min Won   +9 more
wiley   +1 more source

Enhancing Speech Recognition Using Improved Particle Swarm Optimization Based Hidden Markov Model

The Scientific World Journal, 2014
Enhancing speech recognition is the primary intention of this work. In this paper a novel speech recognition method based on vector quantization and improved particle swarm optimization (IPSO) is suggested. The suggested methodology contains four stages,
Lokesh Selvaraj, Balakrishnan Ganesan
doaj   +1 more source

Distributed Vector Quantization Based on Kullback-Leibler Divergence

Entropy, 2015
The goal of vector quantization is to use a few reproduction vectors to represent original vectors/data while maintaining the necessary fidelity of the data.
Pengcheng Shen, Chunguang Li, Yiliang Luo   +2 more
doaj   +1 more source