• Publications
  • Influence
Saliency Detection: A Spectral Residual Approach
  • Xiaodi Hou, L. Zhang
  • Computer Science
  • IEEE Conference on Computer Vision and Pattern…
  • 17 June 2007
The ability of human visual system to detect visual saliency is extraordinarily fast and reliable. However, computational modeling of this basic intelligent behavior still remains a challenge. ThisExpand
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Dynamic visual attention: searching for coding length increments
A visual attention system should respond placidly when common stimuli are presented, while at the same time keep alert to anomalous visual inputs. In this paper, a dynamic visual attention modelExpand
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Bayesian CP Factorization of Incomplete Tensors with Automatic Rank Determination
CANDECOMP/PARAFAC (CP) tensor factorization of incomplete data is a powerful technique for tensor completion through explicitly capturing the multilinear latent factors. The existing CP algorithmsExpand
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Distinct patterns of SSR distribution in the Arabidopsis thaliana and rice genomes
BackgroundSimple sequence repeats (SSRs) in DNA have been traditionally thought of as functionally unimportant and have been studied mainly as genetic markers. A recent handful of studies have shown,Expand
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Edgel index for large-scale sketch-based image search
Retrieving images to match with a hand-drawn sketch query is a highly desired feature, especially with the popularity of devices with touch screens. Although query-by-sketch has been extensivelyExpand
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Bayesian Robust Tensor Factorization for Incomplete Multiway Data
We propose a generative model for robust tensor factorization in the presence of both missing data and outliers. The objective is to explicitly infer the underlying low-CANDECOMP/PARAFAC (CP)-rankExpand
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Neurophysiological substrates of stroke patients with motor imagery-based brain-computer interface training
We investigated the efficacy of motor imagery-based Brain Computer Interface (MI-based BCI) training for eight stroke patients with severe upper extremity paralysis using longitudinal clinicalExpand
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Tensor Ring Decomposition
Tensor networks have in recent years emerged as the powerful tools for solving the large-scale optimization problems. One of the most popular tensor network is tensor train (TT) decomposition thatExpand
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DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data
BackgroundGrowing concerns about increasing rates of antibiotic resistance call for expanded and comprehensive global monitoring. Advancing methods for monitoring of environmental media (e.g.,Expand
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Credit Card Fraud Detection Using Convolutional Neural Networks
Credit card is becoming more and more popular in financial transactions, at the same time frauds are also increasing. Conventional methods use rule-based expert systems to detect fraud behaviors,Expand
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