Results 71 to 80 of about 70,489 (181)
Approximate Nearest Neighbor Fields in Video
, 2015 We introduce RIANN (Ring Intersection Approximate Nearest Neighbor search), an algorithm for matching patches of a video to a set of reference patches in real-time.
Ben-Zrihem, Nir, Zelnik-Manor, Lihi
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Approximate Nearest Neighbor Search in $\ell_p$
, 2013 We present a new locality sensitive hashing (LSH) algorithm for $c$-approximate nearest neighbor search in $\ell_p$ with ...
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Bolt: Accelerated Data Mining with Fast Vector Compression
, 2017 Vectors of data are at the heart of machine learning and data mining. Recently, vector quantization methods have shown great promise in reducing both the time and space costs of operating on vectors.
Blalock, Davis W, Guttag, John V
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Hole Filling for View Synthesis Using Depth Guided Global Optimization
IEEE Access, 2018 View synthesis is an effective way to generate multi-view contents from a limited number of views, and can be utilized for 2-D-to-3-D video conversion, multi-view video compression, and virtual reality. In the view synthesis techniques, depth-image-based
Guibo Luo, Yuesheng Zhu
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High-dimensional approximate nearest neighbor: k-d Generalized Randomized Forests [PDF]
, 2016 We propose a new data-structure, the generalized randomized kd forest, or kgeraf, for approximate nearest neighbor searching in high dimensions. In particular, we introduce new randomization techniques to specify a set of independently constructed trees ...
Avrithis, Yannis +2 more
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, 2018 Approximate nearest neighbor (ANN) search has achieved great success in many tasks. However, existing popular methods for ANN search, such as hashing and quantization methods, are designed for static databases only.
Tsang, Ivor W., Xu, Donna, Zhang, Ying
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Tree-based Search Graph for Approximate Nearest Neighbor Search
, 2022 Nearest neighbor search supports important applications in many domains, such as database, machine learning, computer vision. Since the computational cost for accurate search is too high, the community turned to the research of approximate nearest neighbor search (ANNS). Among them, graph-based algorithm is one of the most important branches.
Fan, Xiaobin +4 more
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Joint K-Means quantization for Approximate Nearest Neighbor Search
2016 23rd International Conference on Pattern Recognition (ICPR), 2016 Recently, Approximate Nearest Neighbor (ANN) Search has become a very popular approach for similarity search on large-scale datasets. In this paper, we propose a novel vector quantization method for ANN, which introduces a joint multi-layer K-Means clustering solution for determination of the codebooks.
Ozan, Ezgi Can +2 more
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Optimizing Matrix-Vector Operations With CGLA for High-Performance Approximate k-NN Search
IEEE AccessIn this paper, we propose a novel approach to accelerating approximate k-nearest neighbor (k-NN) search-a crucial operation in modern vector databases such as OpenSearch, ElasticSearch, Pinecone, and Milvus.
Dohyun Kim, Yasuhiko Nakashima
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Semi-supervised hash learning method with consistency-based dimensionality reduction
Advances in Mechanical Engineering, 2019 With the explosive growth of surveillance data, exact match queries become much more difficult for its high dimension and high volume. Owing to its good balance between the retrieval performance and the computational cost, hash learning technique is ...
Fang Lv +3 more
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