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This paper presents a kernel-based extreme learning machine (KELM) modeling method for speed decision making of autonomous land vehicles (ALVs) on rural roads. The model is obtained offline via the KELM algorithm using a small number of typical samples collected by an ALV platform on rural roads from experienced drivers. Compared with other typical machine learning algorithms such as support vector...
For a practical intracranial brain computer interface (BCI), minimizing the invasiveness of the electrode implantation is crucial. In this study, we used only one intracranial electrode to implement an online BCI for fast typing. When the subject attended the virtual button containing visual motion stimuli, prominent responses were elicited at the stereo-EEG (SEEG) electrodes within the fMRI defined...
This is a set of research exploring using animation in the Massive Open Online Course (MOOC) / Small Private Online Course (SPOC) for learning information security. We established an Information Security SPOC course, with animations made of GoAnimate for learning. The course content was largely based on the standard of the Certified Information Systems Auditor (CISA) from Information Systems Audit...
In this paper we proposed a metric learning-based method to extract collapsed buildings from post-earthquake PolSAR imagery. In this method, eight building and orientation related features, including entropy H, the average scattering angle α, anisotropy A, the circular polarization correlation coefficient ρ and the four scattering powers of Yamaguchi 4 component decomposition with a rotation of the...
Face super-resolution is the specific super-resolution problem based on the property of facial images, which reconstructs a high-resolution facial image from a low-resolution input. Based on the observation that faces are made up of several relatively independent parts such as eyes, noses and mouths, we propose an example-based face hallucination framework which includes correlation-constrained non-negative...
In this paper, we present a study of extracting urban areas from Polarimetric Synthetic Aperture Radar (PolSAR) images using only positive samples. We solve this problem by learning a standard binary classifier (urban/non-urban) given an incomplete set of positive samples (urban) and a set of unlabeled samples (some of which are urban and some of which are non-urban) based on the work of Elkan and...
Music Information Retrieval (MIR) is an interdisciplinary field that facilitates indexing and content-based organization of music databases. Music classification and clustering is one of the major topics in MIR. Music can be defined as `organized sound'. The highly ordered temporal structure of music suggests it should be amendable to analysis by a novel spiking neural network paradigm: the liquid...
In this work, it is the first time that a biologically real neural circuitry is used to model the chemotaxis behaviors of the nematode Caenorhabditis elegans (C. elegans), such as food attraction, toxin avoidance, or multi-tasks behaviors. The use of biological neural network becomes feasible because the structure and connectivity of the C. elegans' nerve system have been completely understood through...
In this paper, a new synchronization receiver architecture for continuous phase modulation (CPM) and relevant carrier phase and symbol timing recovery methods based on frame synchronization and fractional-spaced frequency domain equalization (FDE) are proposed. With frame synchronization and fractional-spaced FDE, frequency selective fading can be equalized for the up-sampled CPM signal. At the same...
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