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This paper proposes a novel unsupervised multi-dimensional scaling (MDS) method to visualize high-dimensional data and their relations in a low-dimensional (e.g., 2D) space. Different from traditional MDS approaches where the main purpose is to embed high-dimensional data into a low-dimensional space, this study aims to both embed data into a low-dimensional space and reveal data relations, thus providing...
We proposed a novel model to predict human's visual attention when free-viewing webpages. Compared with natural images, webpages are usually full of salient regions such as logos, text, and faces, while few of them attract human's attention in a short sight. Moreover, webpages perform distinct viewing patterns which are quite different from the natural images. In this paper, we introduced multi-features...
Dynamic videos are viewed fundamentally different from static images. Besides spatial features, motion feature also plays an important role as a temporal factor. Most existing video saliency models usually employ optical flow to represent the motion feature. However, optical flow often suffers from the discontinuity problem. And we also notice that human fixations in one single video frame are much...
Traditional data processing algorithms are usually not capable to process big data. As matter of fact, usually big data is being defined as such which cannot be processed with traditional techniques. At the same time a progress of technology makes that humans are now overwhelm by big data. One way of processing big data is to use deep neural networks, which are difficult to train so often a combination...
In this paper, a new algorithm for visualization of high-multidimensional data is described. The algorithm follows several steps. At first, centers representing several categories are selected, and Euclidean distances between these centers are calculated in a high-dimensional space. Then these centers are placed in a 2-dimensional space in such a way that distances in this 2-dimensional space are...
With the increasing popularity of Wireless Sensor Networks (WSN), indoor localization has become a key research challenge, since it is crucial to locate the sensors in order to analyze the sensor data in their spatial and temporal contexts. The paper presents a novel method to visualize the position and trajectory of a dynamic WSN using ZigBee's Received Signal Strength Indicator (RSSI) in a map-based...
In this paper, a novel method is proposed to perform saliency detection in news video. This method comprises bottom-up attention model which considers low level features to produce bottom-up saliency map and top-down attention model which utilizes high level factors to generate top-down saliency map. In bottom-up attention model, color image is represented as quaternion. Then the quaternion discrete...
For general airplane design, the research fund is limited and the research period is short. Applying the efficient and intuitive visualization techniques is beneficial to solve this problem. This paper visually simulated the environment around the choice of the aircraft's flight parameters, airplane taking off and landing and the cockpit view. This research established an airport environment visualization...
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