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Composite structures, 2021
Filament-wound cylinder always demonstrates diverse performances due to the different designed parameters. This paper aims to provide a hybrid method for optimizing the winding angle and fiber volume content of a composite cylinder under internal ...
Chao Kang +6 more
semanticscholar +1 more source
Filament-wound cylinder always demonstrates diverse performances due to the different designed parameters. This paper aims to provide a hybrid method for optimizing the winding angle and fiber volume content of a composite cylinder under internal ...
Chao Kang +6 more
semanticscholar +1 more source
Kernelized Locality-Sensitive Hashing
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012Fast retrieval methods are critical for many large-scale and data-driven vision applications. Recent work has explored ways to embed high-dimensional features or complex distance functions into a low-dimensional Hamming space where items can be efficiently searched.
Brian Kulis, Kristen Grauman
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Science of the Total Environment, 2019
Physically-based urban wash-off models are a promising means of studying the transport of finer suspended solids and their associated pollutants during rain events, considering spatial and temporal heterogeneities.
J. Naves +4 more
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Physically-based urban wash-off models are a promising means of studying the transport of finer suspended solids and their associated pollutants during rain events, considering spatial and temporal heterogeneities.
J. Naves +4 more
semanticscholar +1 more source
Distributed Locality Sensitivity Hashing
2010 7th IEEE Consumer Communications and Networking Conference, 2010In this paper, we present DLSH Distributed Locality Sensitive Hashing, a similar-data search technology. The huge growth in the size of video content has broken the traditional multi-media index hosting and look-up solutions, these are not able to scale to the size of the current and projected index requirements.
Smita Wadhwa, Pawan Gupta
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In Defense of Locality-Sensitive Hashing
IEEE Transactions on Neural Networks and Learning Systems, 2018Hashing-based semantic similarity search is becoming increasingly important for building large-scale content-based retrieval system. The state-of-the-art supervised hashing techniques use flexible two-step strategy to learn hash functions. The first step learns binary codes for training data by solving binary optimization problems with millions of ...
Kun Ding 0001 +4 more
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Fast locality-sensitive hashing
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, 2011Locality-sensitive hashing (LSH) is a basic primitive in several large-scale data processing applications, including nearest-neighbor search, de-duplication, clustering, etc. In this paper we propose a new and simple method to speed up the widely-used Euclidean realization of LSH.
Anirban Dasgupta 0001 +2 more
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On the Local Sensitivity of the Lyapunov Equations
2001This paper presents a new local perturbation bound for the continuous-time Lyapunov matrix equations, which is not formulated in terms of condition numbers. The new bound is a nonlinear, first order homogeneous function of the absolute perturbations in the data and is sharper than the linear local bounds based on condition numbers.
Suzanne Lesecq +2 more
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Locality-Sensitive Hashing for Chi2 Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012In the past 10 years, new powerful algorithms based on efficient data structures have been proposed to solve the problem of Nearest Neighbors search (or Approximate Nearest Neighbors search). If the Euclidean Locality Sensitive Hashing algorithm, which provides approximate nearest neighbors in a euclidean space with sublinear complexity, is probably ...
Gorisse, David +2 more
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An explicit study of local ozone budget and NOx-VOCs sensitivity in Shenzhen China
, 2020In China, a significant reduction in primary pollution has been observed due to the Clean Air Action since 2013, and ozone pollution has become increasingly prominent over the past years.
Dan Yu +15 more
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