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Entropy-optimized deep weighted product quantization for image retrieval
Hashing and quantization have greatly succeeded by benefiting from deep learning for large-
scale image retrieval. Recently, deep product quantization methods have attracted wide …
scale image retrieval. Recently, deep product quantization methods have attracted wide …
A survey on efficient processing of similarity queries over neural embeddings
Y Wang - arxiv preprint arxiv:2204.07922, 2022 - arxiv.org
Similarity query is the family of queries based on some similarity metrics. Unlike the
traditional database queries which are mostly based on value equality, similarity queries aim …
traditional database queries which are mostly based on value equality, similarity queries aim …
Unleashing the full potential of product quantization for large-scale image retrieval
Y Liang, S Zhang, LK Li… - Advances in Neural …, 2023 - proceedings.neurips.cc
Due to its promising performance, deep hashing has become a prevalent method for
approximate nearest neighbors search (ANNs). However, most of current deep hashing …
approximate nearest neighbors search (ANNs). However, most of current deep hashing …
Quantization
S Bruch - Foundations of Vector Retrieval, 2024 - Springer
In a vector retrieval system, it is usually not enough to process queries as fast as possible. It
is equally as important to reduce the size of the index by compressing vectors. Compression …
is equally as important to reduce the size of the index by compressing vectors. Compression …
[HTML][HTML] Approximate nearest neighbor search using enhanced accumulative quantization
L Ai, H Cheng, X Wang, C Chen, D Liu, X Zheng… - Electronics, 2022 - mdpi.com
Approximate nearest neighbor (ANN) search is fundamental for fast content-based image
retrieval. While vector quantization is one key to performing an effective ANN search, in …
retrieval. While vector quantization is one key to performing an effective ANN search, in …
Image compression based on vector quantization and optimized code-book design using Genetic Mating Influenced Slime Mould (GMISM) algorithm
Large amounts of storage are required to store the recent massive influx of fresh
photographs that are uploaded to the internet. Many analysts created expert image …
photographs that are uploaded to the internet. Many analysts created expert image …
Product quantization to reduce entropy of labels for fast and accurate image retrieval
F Nakamura, R Harakawa… - 2021 Asia-Pacific Signal …, 2021 - ieeexplore.ieee.org
Product quantization (PQ) is a popular technique for fast image retrieval from a large-scale
database. PQ methods quantize image features into short codes and realize fast retrieval …
database. PQ methods quantize image features into short codes and realize fast retrieval …
[PDF][PDF] Quantization of Product using Collaborative Filtering Based on Cluster
E Sankar, L Karthik, KV Sastry - academia.edu
Because of strict response-time constraints, efficiency of top-k recommendation is crucial for
real-world recommender systems. Locality sensitive hashing and index-based methods …
real-world recommender systems. Locality sensitive hashing and index-based methods …
Recuperação semântica de paisagens sonoras usando banco de dados vetoriais
AD Peralta, EM dos Santos, J **e… - … de Computação Aplicada …, 2024 - sol.sbc.org.br
A recuperação semântica de paisagens sonoras emerge como um componente crucial para
monitorar ecossistemas. No entanto, devido à natureza contínua do monitoramento ao …
monitorar ecossistemas. No entanto, devido à natureza contínua do monitoramento ao …