منابع مشابه
Semantic hashing
We show how to learn a deep graphical model of the word-count vectors obtained from a large set of documents. The values of the latent variables in the deepest layer are easy to infer and give a much better representation of each document than Latent Semantic Analysis. When the deepest layer is forced to use a small number of binary variables (e.g. 32), the graphical model performs “semantic ha...
متن کاملUnsupervised Semantic Deep Hashing
In recent years, deep hashing methods have been proved to be efficient since it employs convolutional neural network to learn features and hashing codes simultaneously. However, these methods are mostly supervised. In real-world application, it is a time-consuming and overloaded task for annotating a large number of images. In this paper, we propose a novel unsupervised deep hashing method for ...
متن کاملDeep Semantic-Preserving and Ranking-Based Hashing for Image Retrieval
Hashing techniques have been intensively investigated for large scale vision applications. Recent research has shown that leveraging supervised information can lead to high quality hashing. However, most existing supervised hashing methods only construct similarity-preserving hash codes. Observing that semantic structures carry complementary information, we propose the idea of cotraining for ha...
متن کاملContent-Based Image Retrieval using Semantic Assisted Visual Hashing
This is a new technology to support scalable content-based image retrieval (CBIR]), hashing has been recently been focused and future directions of research domain. In this paper, we propose a unique unsupervised visual hashing approach called semantic-assisted visual hashing (SAVH). Distinguished from semi-supervised and supervised visual hashing, its core idea emphatically extracts the rich s...
متن کاملSemantic Topic Multimodal Hashing for Cross-Media Retrieval
Multimodal hashing is essential to cross-media similarity search for its low storage cost and fast query speed. Most existing multimodal hashing methods embedded heterogeneous data into a common low-dimensional Hamming space, and then rounded the continuous embeddings to obtain the binary codes. Yet they usually neglect the inherent discrete nature of hashing for relaxing the discrete constrain...
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ژورنال
عنوان ژورنال: International Journal of Approximate Reasoning
سال: 2009
ISSN: 0888-613X
DOI: 10.1016/j.ijar.2008.11.006