Results 11 to 20 of about 80,492 (210)
Unsupervised Hashing with Contrastive Information Bottleneck [PDF]
International Joint Conference on Artificial Intelligence, 2021 Many unsupervised hashing methods are implicitly established on the idea of reconstructing the input data, which basically encourages the hashing codes to retain as much information of original data as possible.
Zexuan Qiu +4 more
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From Image Hashing to Video Hashing [PDF]
, 2010 Perceptual hashing is a technique for content identification and authentication. In this work, a frame hash based video hash construction framework is proposed. This approach reduces a video hash design to an image hash design, so that the performance of the video hash can be estimated without heavy simulation.
Weng, Li, Preneel, Bart
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A Survey on Deep Hashing Methods [PDF]
ACM Transactions on Knowledge Discovery from Data, 2020 Nearest neighbor search aims at obtaining the samples in the database with the smallest distances from them to the queries, which is a basic task in a range of fields, including computer vision and data mining.
Xiao Luo +6 more
semanticscholar +1 more source
Performance Analysis of Sequential Cuckoo Hashing under Light of Switching Cost [PDF]
Computer Science Journal of MoldovaCuckoo Hashing has been considered the state of the art since its origin. In Cuckoo Hashing, the search operation is executed sequentially in the tables, and thus, Cuckoo Hashing is Sequential Cuckoo Hashing.
Rajeev Ranjan Kumar Tripathi +2 more
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BRICS Report Series, 2001 We present a simple and efficient dictionary with worst case constant lookup time, equaling the theoretical performance of the classic dynamic perfect hashing scheme of Dietzfelbinger et al. (<em>Dynamic perfect hashing: Upper and lower bounds. SIAM J. Comput., 23(4):738-761, 1994</em>).
Rasmus Pagh, Flemming Friche Rodler
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IEEE Access, 2019 With the rapid growth of multimedia data (e.g., image, audio, and video) on the Web, the learning-based hashing techniques, such as deep supervised hashing, have proven to be very efficient for large-scale multimedia search.
Zhan Yang +3 more
doaj +1 more source
Symbolic Representation and Learning With Hyperdimensional Computing
Frontiers in Robotics and AI, 2020 It has been proposed that machine learning techniques can benefit from symbolic representations and reasoning systems. We describe a method in which the two can be combined in a natural and direct way by use of hyperdimensional vectors and ...
Anton Mitrokhin +4 more
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AAU-Net: Attention-Based Asymmetric U-Net for Subject-Sensitive Hashing of Remote Sensing Images
Remote Sensing, 2021 The prerequisite for the use of remote sensing images is that their security must be guaranteed. As a special subset of perceptual hashing, subject-sensitive hashing overcomes the shortcomings of the existing perceptual hashing that cannot distinguish ...
Kaimeng Ding +5 more
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TransHash: Transformer-based Hamming Hashing for Efficient Image Retrieval [PDF]
International Conference on Multimedia Retrieval, 2021 Deep hashing has gained growing popularity in approximate nearest neighbor search for large-scale image retrieval. Until now, the deep hashing for the image retrieval community has been dominated by convolutional neural network architectures, e.g. Resnet
Yongbiao Chen +7 more
semanticscholar +1 more source
Algorithm of locality sensitive hashing bit selection based on feature selection
大数据, 2021 Locality sensitive hashing is one of the most popular information retrieval methods, which needs to generate long hashing bits to meet the retrieval requirement.However, a long hashing bits requires huge storage space, and contains plenty of redundant ...
Wenhua ZHOU, Huawen LIU, Enhui LI
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