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Interactive graph cuts are widely used in object seg-mentation but with some disadvantages: 1) Manual interactions may cause inaccurate or even incorrect seg-mentation results and involve more interactions especially for novices. 2) In some situations, the manual interactions are infeasible. To overcome these disadvantages , we propose a novel approach,(More)
To make sure that microbial fuel cells (MFCs) are more convenient to stack, a baffled single-chambered MFC with two groups of electrodes sharing only one anode chamber was designed and the performance was examined. The experiments showed that the prototype MFC generated electrical power (maximum of 133 mW/m(2)) while removing up to 88% of chemical oxygen(More)
[1] Land surface emissivity (LSE) in the infrared (IR) window region (8–12 mm) governs the thermal emissions from the Earth's surface. Many LSE databases, retrieved from various satellite instruments, are available for studying climate, Earth‐atmosphere interaction, weather, and the environment. The precision (standard deviation) and accuracy (bias) of(More)
Most broadcast stations rely on TV logos to claim video content ownership or visually distinguish the broadcast from the interrupting commercial block. Detecting and tracking a TV logo is of interest to TV commercial skipping applications and logo-based broadcasting surveillance (abnormal signal is accompanied by logo absence). Pixel-wise difference(More)
In this paper, we present a variational Bayes (VB) approach for image segmentation. First, image is mod-eled by a mixture model, and then with the techniques of factor analyzer, the underlying structure of image content is inferred automatically. Different from the traditional EM algorithm that seriously suffers from component number selection, the proposed(More)
Image segmentation is a fundamental process in remote sensing image interpretation. It is the basis of the image understanding, such as the region-based change detection for maps updating, the target recognition, and so on [3, 4]. This problem can be seen as a pattern classification application by employing a statistical framework, in which Bayesian(More)