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This paper presents a Semantic Attribute assisted video SUMmarization framework (SASUM). Compared with traditional methods, SASUM has several innovative features. Firstly, we use a natural language processing tool to discover a set of keywords from an image and text corpora to form the semantic attributes of visual contents. Secondly, we train a deep convolution neural network to extract visual features...
This paper is aimed at the difficult problem of multi region segmentation of weld pool image, analyzed The difficulty of edge extraction in the inner region of the weld pool. According to the characteristics between pixel neighborhood space and neighbor pixel correlation, based on local standard deviation, presented a noise suppression, edge enhancement of the weld pool image multi region division...
Multisource remote sensing data can provide complementary information for object information extraction. However, the increasing of feature types and the dimensions, it is critical for OBIA (Object- Based Image Analysis, OBIA) that the identification of features and the separability between classes. Automatic the features selection and thresholds calculation can avoid time-consuming trial-and-error...
Retinal vessel delineation is a hot research topic owing to its importance in a lot of clinic application. Several methods have been proposed in the past decades. Here we will present a new supervised method for retinal vessel segmentation. The method is designed to explore the complex relationship between retinal images and their corresponding vessel label maps. Specifically, in order to build a...
Accurate liver segmentation is an essential and crucial step for computer-aided liver disease diagnosis and surgical planning. In this paper, a new coarse-to-fine method is proposed to segment liver for abdominal computed tomography (CT) images. This hierarchical framework consists of rough segmentation and refined segmentation. The rough segmentation is implemented based on a kernel fuzzy C-means...
Accurate segmentation of breast on MR images is an essential and crucial step for computer-aided breast disease diagnosis and surgical planning. In this paper, an effective approach is proposed for segmenting the breast image into different regions, each corresponding to a different tissue. The segmentation work flow comprises two key steps. Firstly, we use the threshold-based method and morphological...
In this paper, we propose an automatic approach to segment object from stereo videos, for which the viewpoints are widely apart. We first present a novel saliency analysis to emphasize the foreground object. The saliency map is estimated by combining the depth information recovered by feature matching and the boundary information revealed by color segmentation. The object mask is extracted initially...
The gridding is an essential task for DNA microarray image analysis which will definitely affect the spot segmentation and intensity extraction. The accuracy and reliability of existing gridding methods depend on the artificial experience value owing to they can not dynamically determine the required processing parameters. In this paper, the gridding problem is turned into an optimizing problem by...
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