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Deep Learning-Based Image Retrieval With Unsupervised Double Bit Hashing
IEEE Transactions on Circuits and Systems for Video Technology, 2023Unsupervised image hashing is a widely used technique for large-scale image retrieval. This technique maps an image to a finite length of binary codes without extensive human-annotated data for compact storage and effective semantic retrieval. This study
Heri Prasetyo +2 more
exaly +2 more sources
Double-Bit Quantization and Index Hashing for Nearest Neighbor Search
IEEE Transactions on Multimedia, 2019As binary code is storage efficient and fast to compute, it has become a trend to compact real-valued data to binary codes for the nearest neighbors (NN) search in a large-scale database.
Zhendong Mao +2 more
exaly +2 more sources
International Conference on Intelligent Transportation, Big Data and Smart City, 2020
When processing the high-dimension and massive data collected in the production process of ultra-precision machining tool, there is the issue of low efficiency in query operation of multi-key query and time range.
Shenghui Liu
exaly +2 more sources
When processing the high-dimension and massive data collected in the production process of ultra-precision machining tool, there is the issue of low efficiency in query operation of multi-key query and time range.
Shenghui Liu
exaly +2 more sources
Double locality sensitive hashing Bloom filter for high-dimensional streaming anomaly detection
Information Processing and Management, 2023Ruliang Xiao
exaly +2 more sources
Engineering Applications of Artificial Intelligence
Yunqi Lei, Shan Zhenpei, Defu Zhang
exaly +2 more sources
Yunqi Lei, Shan Zhenpei, Defu Zhang
exaly +2 more sources
Double-Hashing Operation Mode for Encryption
2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), 2017Block ciphers, hash-based encryption, and public-key ciphers are examples of data encryption techniques with different desired features. Strong block ciphers, like AES, must run in some mode of operation to encrypt data larger than the block size. Public-key ciphers, like RSA, are costly and usually used for key-sharing rather than encrypting the data ...
Sultan Almuhammadi, Ahmad Amro
semanticscholar +2 more sources
Peeling arguments and double hashing
2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2012The analysis of several algorithms and data structures can be reduced to the analysis of the following greedy “peeling” process: start with a random hypergraph; find a vertex of degree at most k, and remove it and all of its adjacent hyperedges from the graph; repeat until there is no suitable vertex.
M. Mitzenmacher, J. Thaler
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Model Size Reduction Using Frequency Based Double Hashing for Recommender Systems
ACM Conference on Recommender Systems, 2020Deep Neural Networks (DNNs) with sparse input features have been widely used in recommender systems in industry. These models have large memory requirements and need a huge amount of training data.
Caojin Zhang +12 more
semanticscholar +1 more source
Deep Double Center Hashing for Face Image Retrieval
Chinese Conference on Pattern Recognition and Computer Vision, 2021Hashing is an effective and widely used technology for fast approximate nearest neighbor search in large-scale images. In recent years, it has been combined with a powerful feature learning model, convolutional neural network(CNN), to boost the efficiency of large-scale image retrieval. In this paper, we introduce a new Deep Double Center Hashing (DDCH)
Xin Fu, Wenzhong Wang, Jin Tang
semanticscholar +3 more sources