نتایج جستجو برای: hashing
تعداد نتایج: 4633 فیلتر نتایج به سال:
Deep supervised hashing has emerged as an influential solution to large-scale semantic image retrieval problems in computer vision. In the light of recent progress, convolutional neural network based hashing methods typically seek pair-wise or triplet labels to conduct the similarity preserving learning. However, complex semantic concepts of visual contents are hard to capture by similar/dissim...
Propositional model counting is a fundamental problem in artificial intelligence with a wide variety of applications, such as probabilistic inference, decision making under uncertainty, and probabilistic databases. Consequently, the problem is of theoretical as well as practical interest. When the constraints are expressed as DNF formulas, Monte Carlo-based techniques have been shown to provide...
Video hashing is a common solution for content-based video retrieval by encoding high-dimensional feature vectors into short binary codes. Videos not only have spatial structure inside each frame but also have temporal correlation structure between frames, while the latter has been largely neglected by many existing methods. Therefore, in this paper we propose to perform video hashing by incorp...
The trend toward networks becoming larger and faster, and addresses increasing in size, has impelled a need to explore alternatives for fast address recognition. Hashing is one such alternative which can help minimize the address search time in adapters, bridges, routers, gateways, and name servers. Using a trace of address references, we compared the e ciency of several di erent hashing functi...
Recently, hashing video contents for fast retrieval has received increasing attention due to the enormous growth of online videos. As the extension of image hashing techniques, traditional video hashing methods mainly focus on seeking the appropriate video features but pay little attention to how the video-specific features can be leveraged to achieve optimal binarization. In this paper, an end...
Hashing has emerged as a popular technique for fast nearest neighbor search in gigantic databases. In particular, learning based hashing has received considerable attention due to its appealing storage and search efficiency. However, the performance of most unsupervised learning based hashing methods deteriorates rapidly as the hash code length increases. We argue that the degraded performance ...
Cross-view retrieval, which focuses on searching images as response to text queries or vice versa, has received increasing attention recently. Crossview hashing is to efficiently solve the cross-view retrieval problem with binary hash codes. Most existing works on cross-view hashing exploit multiview embedding method to tackle this problem, which inevitably causes the information loss in both i...
This study pioneers a new way to study the performance of hashing algorithms by evaluating their queueing behavior. We examine hashing as applied to URL routing used in Content Distribution Networks (CDNs). URL routing tables can be built as self-adjusting hash tables to reduce network bandwidth consumption in CDNs and at the same time take advantage of the high temporal locality of Web documen...
Minwise hashing is a fundamental and one of the most successful hashing algorithm in the literature. Recent advances based on the idea of densification (Shrivastava & Li, 2014a;c) have shown that it is possible to compute k minwise hashes, of a vector with d nonzeros, in mere (d + k) computations, a significant improvement over the classical O(dk). These advances have led to an algorithmic impr...
In social networks, heterogeneous multimedia data correlate to each other, such as videos and their corresponding tags in YouTube and image-text pairs in Facebook. Nearest neighbor retrieval across multiple modalities on large data sets becomes a hot yet challenging problem. Hashing is expected to be an efficient solution, since it represents data as binary codes. As the bit-wise XOR operations...
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