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A novel algorithm using modified statistical region merging (MSRM) for Synthetic Aperture Radar (SAR) image change detection is proposed in this paper. The statistical region merging algorithm is modified to cope with the speckles of SAR images. A new statistical predicate variable is introduced to control the merging process to end up with three classes in the final map. Comparative experiments show...
Cuboid detection is an essential step for understanding 3D structure of scenes. As most of indoor scene cuboids are actually objects, we propose in this paper an object-based approach to detect 3D cuboids in indoor RGB-D images. The proposed approach is learning-free and can handle general object classes rather than a limited pre-defined category set. In our approach, we first apply an extended version...
In this paper, we propose a novel deep learning based method for video semantic segmentation. Specially, we utilize 3D convolution neural network (3D CNN) to learn discriminative hierarchical features from spatial-temporal volumes for accurate pixel labelling. The learned features are capable of capturing both appearance and motion information. To align the pixel labels along real object boundaries,...
Shape information is essential in medical image analysis as the anatomical structures usually have strong shape characteristics. Shape priors can resolve ambiguities when the low level appearance is weak or misleading due to imaging artifacts and diseases. In this paper, we propose a shape prior model based on the Gaussian-Bernoulli Restricted Boltzmann Machine (GB-RBM). This powerful generative model...
Virtual colonoscopy (VC) is a safe and fast medical imaging procedure to screen the colon for polyps. And it has become very popular recently. Colon segmentation is a necessary and important step of such an examination procedure. In this paper, an automatic colon segmentation method is proposed. The fluid inside the colon is first identified and removed based on its characteristic of horizontal surface...
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