vector-quantization

🔴 MiniSom is a minimalistic implementation of the Self Organizing Maps

Using ideas from product quantization for state-of-the-art neural network compression.

Dice.com repo to accompany the dice.com 'Vectors in Search' talk by Simon Hughes, from the Activate 2018 search conference, and the 'Searching with Vectors' talk from Haystack 2019 (US). Builds upon my conceptual search and semantic search work from 2015

🙃Implementation of vector quantization algorithms, codes for Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search..

Pytorch Implementation of "Neural Discrete Representation Learning"

🤣A framework for index based similarity search.

A RoQ video playback system for the Sega Dreamcast video game console

PyTorch implementation of VQ-VAE applied on CIFAR10 dataset

implementation of the k-means-u* clustering algorithm

Automatically exported from code.google.com/p/speech-recognition-java-hidden-markov-model-vq-mfcc

Data cleanse, clustering with Vector Quantization and Adaptive Resonance Theory

Lossy Image Compression using Vector Quantization and K-Means Clustering.

Linear Predictive Coding Vector Quantization and Hidden Markov Modeling for speech recognition

Speaker Recognition using MFCC feature vectors and GLA vector quantization models

Automatic Speech Recognition library for my BTech Project.

An automatic speaker recognition system built from digital signal processing tools, Vector Quantization and LBG algorithm

Compression of an image by Self organizing map.

Applying multiple VQ along the feature axis

A Java program that implments Vector Quantization LBG Algorithm on greyscale RAW images, user determines the compression level.

Using C++ to implement Vector Quantization Encoder

Compression of an image by using variable block-size for vector quantization.

Implementation of Compression and Learning Algorithms

We'll be trying to compress an image using VQ. Vector quantization (VQ) is a lossy data compression method based on the principle of block coding. It is a fixed-to-fixed length algorithm.

A low-complexity VQ image codec

Under Armour Innovation Project Search

Automatically exported from code.google.com/p/mouse-gesture-recognition-java-hidden-markov-model

Two lossy algorithms, Discrete Wavelet Transform (DWT) and Vector Quantization (VQ) are added together to compress medical images and see their performance.

Repository for uni team project. Vector quantization in Python

A Java program that implements Vector Quantization

k-means clustering is a method of vector quantization, originally from signal processing, that is popular for cluster analysis in data mining. k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster.