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Classification in remote sensing, similar to semantic segmentation in computer vision, is aimed to assign a label to each pixel in images to indicate which class it belongs to. Fully convolutional networks (FCN), one of semantic segmentation methods, is proposed to tackle this problem in fully PolSAR images in this paper. To exploit the polarimetric information in PolSAR images, H-A-α polarimetric...
This paper presents TweeVist, a geo-tweet visualization system to support users grasp event happens over time and space from tweets while they browse any web pages based on spatio-temporal analysis. TweeVist presents a tag cloud of tweets in different time periods are associated with web pages based on detected events. In order to detect events, the system extracts normal events (e.g., crowded restaurants,...
In this paper, we propose a novel method for the automatic detection of fetal head in 2D ultrasound images. Fetal head detection has been a challenging task, as the ultrasound images usually have poor quality, the structures contained in the images are complex, and the gray scale distribution is highly variable. Our approach is based on a deep belief network and a modified circle detection method...
A novel approach is presented to automatically segment the left ventricle in fetal echocardiograms. The proposed approach strategically integrates sparse representation, global constraint, and local refinement algorithms into an active appearance model (AAM) framework. In the training stage, we construct an enhanced AAM texture model to deal with the speckle and texture ambiguities. In the segmentation...
Textural features were extracted from livers' B-mode ultrasonic images to diagnose hepatic fibrosis for chronic hepatitis-B patients (CHB). For a selected region of interest (ROI) of an ultrasonic image, 13 textural parameters based on its gray level co-occurrence matrix (GLCM) were calculated. A Fisher linear classifier was built using 83 images as its training set. The results of the test on 38...
The nuchal translucency (NT) thickness is an important parameter in the diagnosis of fetuses. The previous computerized methods often require manual operations to select the NT region, which leads to the time-consuming problem and the detection variability. In the paper, a hierarchical structural model is proposed for the automated detection of the NT region. Three discriminative classifiers are first...
Electricity demand forecasting is an important index to make power development plan and dispatch the loading of generating units in order to meet system demand. In order to improve the accuracy of the forecasting, we apply the feedforward neural network for electricity demand forecasting. Inspired by the idea of artificial fish swarm algorithm, in this paper we proposed one hybrid evolutionary algorithm...
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