13 research outputs found

    Detecting regions of interest using eye tracking for CBIR

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    Identifying Regions of Interest (ROIs) in images has been shown an effective way to enhance the performance of Content Based Image Retrieval (CBIR). Most existing ROI identification methods are based on salience detection, and the identified ROIs may not be the regions that users are really interested in. While manual selection of ROIs can directly reflect users’ interests, it puts extra cognitive overhead to users. To alleviate these limitations, in this paper, we propose a novel eye-tracking based method to detect ROIs for CBIR, in an unobtrusive way. Experimental results have demonstrated that our model performed effectively compared with various state of the art methods

    Uni-traveling-carrier photodetector with high-contrast grating focusing-reflection mirrors

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    A novel uni-traveling-carrier photodetector (UTC-PD) structure with an integrated focusing-reflection (FR) mirror realized by a non-periodic concentric circular high-contrast grating (NP-CC-HCG), referred to as FR-UTC-PD, is proposed to enhance responsivity in conventional UTC-PDs. The FR-UTC-PD allows improving the responsivity by 36.5% at a 1.55-um wavelength as compared to a UTC-PD without integrated an FR mirror with 84.59% reflectivity. For 40-um-diameter PDs, the obtained 3-dB bandwidths are unaltered with values of 18 GHz at -3.0 V bias voltage. The radio-frequency (RF) output power and photocurrent are -1.77 dBm and 17.56 mA, respectively, at 10 GHz and the -6.0 V bias voltage.Comment: 14 pages, 5 figure
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