• Publications
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The Role of Context for Object Detection and Semantic Segmentation in the Wild
TLDR
We propose a novel deformable part-based model, which exploits both local context around each candidate detection as well as global context at the level of the scene. Expand
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Thinning Methodologies - A Comprehensive Survey
TLDR
A comprehensive survey of thinning methodologies, including iterative deletion of pixels and nonpixel-based methods, is covered. Expand
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A Novel Bayesian Framework for Discriminative Feature Extraction in Brain-Computer Interfaces
  • H. Suk, S. Lee
  • Computer Science, Medicine
  • IEEE Transactions on Pattern Analysis and Machine…
  • 1 February 2013
TLDR
We propose a novel Bayesian framework for discriminative feature extraction for motor imagery classification in an EEG-based BCI in which the class-discriminative frequency bands and the corresponding spatial filters are optimized by means of the probabilistic and information-theoretic approaches. Expand
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Sign Language Spotting with a Threshold Model Based on Conditional Random Fields
TLDR
In this paper, a novel method for designing threshold models in a conditional random field (CRF) model is proposed which performs an adaptive threshold for distinguishing between signs in a vocabulary and nonsign patterns. Expand
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Person authentication from neural activity of face-specific visual self-representation
TLDR
We propose a new biometric system based on the neurophysiological features of face-specific visual self representation in a human brain, which can be measured by ElectroEncephaloGraphy (EEG). Expand
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Applications of Support Vector Machines for Pattern Recognition: A Survey
TLDR
We present a comprehensive survey on applications of Support Vector Machines (SVMs) for pattern recognition. Expand
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A convolutional neural network for steady state visual evoked potential classification under ambulatory environment
TLDR
A convolutional neural network for steady state visual evoked potentials (SSVEPs) classification under ambulatory environment. Expand
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State-space model with deep learning for functional dynamics estimation in resting-state fMRI
TLDR
We propose a novel methodological architecture that combines deep learning and state-space modelling, and apply it to rs-fMRI based Mild Cognitive Impairment (MCI) diagnosis. Expand
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Human action recognition using shape and CLG-motion flow from multi-view image sequences
  • M. Ahmad, S. Lee
  • Mathematics, Computer Science
  • Pattern Recognit.
  • 1 July 2008
TLDR
In this paper, we present a method for human action recognition from multi-view image sequences that uses the combined motion and shape flow information with variability consideration. Expand
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A lower limb exoskeleton control system based on steady state visual evoked potentials.
TLDR
OBJECTIVE We have developed an asynchronous brain-machine interface (BMI)-based lower limb exoskeleton control system based on steady-state visual evoked potentials (SSVEPs). Expand
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