Approximate Nearest Neighbor Search by Residual Vector Quantization [PDF]
Sensors, 2010 A recently proposed product quantization method is efficient for large scale approximate nearest neighbor search, however, its performance on unstructured vectors is limited.
Cheng Wang, Tao Guan, Yongjian Chen
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Accumulative Quantization for Approximate Nearest Neighbor Search. [PDF]
Comput Intell Neurosci, 2022 To further improve the approximate nearest neighbor (ANN) search performance, an accumulative quantization (AQ) is proposed and applied to effective ANN search. It approximates a vector with the accumulation of several centroids, each of which is selected from a different codebook.
Ai L +6 more
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Approximate Nearest Neighbor Search for Low Dimensional Queries [PDF]
Proceedings of the Twenty-Second Annual ACM-SIAM Symposium on Discrete Algorithms, 2010 We study the Approximate Nearest Neighbor problem for metric spaces where the query points are constrained to lie on a subspace of low doubling dimension, while the data is high-dimensional. We show that this problem can be solved efficiently despite the
Har-Peled, Sariel, Kumar, Nirman
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Capacity-Limited Failure in Approximate Nearest Neighbor Search on Image Embedding Spaces [PDF]
Journal of ImagingSimilarity search on image embeddings is a common practice for image retrieval in machine learning and pattern recognition systems. Approximate nearest neighbor (ANN) methods enable scalable similarity search on large datasets, often approaching sub ...
Morgan Roy Cooper, Mike Busch
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Multi-PQTable for Approximate Nearest-Neighbor Search [PDF]
Information, 2019 Image retrieval or content-based image retrieval (CBIR) can be transformed into the calculation of the distance between image feature vectors. The closer the vectors are, the higher the image similarity will be.
Xinpan Yuan +4 more
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ON-NSW: Accelerating High-Dimensional Vector Search on Edge Devices with GPU-Optimized NSW [PDF]
SensorsThe Industrial Internet of Things (IIoT) increasingly relies on vector embeddings for analytics and AI-driven applications such as anomaly detection, predictive maintenance, and sensor fusion.
Taeyoon Park +3 more
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A reliable order-statistics-based approximate nearest neighbor search algorithm [PDF]
IEEE Transactions on Image Processing, 2016 We propose a new algorithm for fast approximate nearest neighbor search based on the properties of ordered vectors. Data vectors are classified based on the index and sign of their largest components, thereby partitioning the space in a number of cones ...
Cozzolino, Davide +2 more
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Leveraging a foundation model zoo for cell similarity search in oncological microscopy across devices [PDF]
Frontiers in OncologyBackgroundCellular imaging analysis using the traditional retrospective approach is extremely time-consuming and labor-intensive. Although AI-based solutions are available, these approaches rely heavily on supervised learning techniques that require high
Gabriel Kalweit +32 more
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Approximate Nearest Neighbor Search Based on Neighbor Graphs with Parameter Adaptation [PDF]
Jisuanji gongcheng, 2022 Approximate Nearest Neighbor Search(ANNS) algorithms based on neighbor graphs typically organize vectors in a database into a neighbor graph structure and obtain the Approximate Nearest Neighbor(ANN) of the query vector by leveraging user-specified ...
GAN Hongnan, ZHANG Kai
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Secure Cloud-Aided Approximate Nearest Neighbor Search on High-Dimensional Data
IEEE Access, 2023 As one fundamental data-mining problem, ANN (approximate nearest neighbor search) is widely used in many industries including computer vision, information retrieval, and recommendation system.
Jia Liu +7 more
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