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Generating a realistic image from a novel viewpoint has always been a key problem in image-based rendering and other related domains. In this paper we utilize the state-of-the-art generative adversarial networks(GAN) to synthesize novel views of a structured scene. Based on our proposed representations for traffic scene, a realistic image of a certain viewpoint can be generated via conditional GANs,...
Creativity is considered as a very important element of the society development. Having entered the big data era, people have been focusing on finding a pathway developing creativity for all applications. In the psychology and education domain, various approaches have been attempted, such as divergent thinking and brain storming. The psychology domain has researched on human's cognitive development...
Wind power prediction is very important to guarantee security and stability of the wind farm and power system operation, and wind speed forecasting is the key to wind power prediction. Due to dramatic changes and shorter collection intervals in wind speed, it generates a larger numbers of samples, which affects modeling time and accuracy. Therefore, a short-term wind speed prediction method based...
This paper investigates the problem of online active learning for training classification models from sequentially arriving data. This is more challenging than conventional online learning tasks since the learner not only needs to figure out how to effectively update the classifier but also needs to decide when is the best time to query the label of an incoming instance given limited label budget...
Speaker recognition in short speech condition is a difficult topic because the length of training and test speech is very short. One of the main disadvantage of the existing methods for speaker recognition is that they need very sufficient data and it's usually impossible in reality applications. In our experiments, the conventional methods with single feature don't make good performance in short...
With the rapid growth of the smart device market, associated security issues become more threatening and diverse than ever before. Due to the limitations of the traditional explicit authentication mechanisms (e.g., Password-based, biometrics), researchers and the industry have been promoting implicit authentication (IA) that does not require explicit user action and potentially enhances user experience...
Adaptation is an essential capability for intelligent robots to work in new environments. In the learning framework of Programming by Demonstration (PbD) and Reinforcement Learning (RL), a robot usually learns skills from a latent feature space obtained by dimension reduction techniques. Because the latent space is optimized for a specific environment during the training phase, it typically contains...
Light field photography provides a revolutionary possibility to reconstruct well-focused iris region from a 4D light-field image. However, such a “shoot and refocus” scheme is time-consuming in practice because it commonly needs to render an image sequence for finding the optimally refocused frame. This paper presents an efficient auto-refocusing iris imaging solution for lenselet-based light-field...
It is estimated that over 8 million cell phones are lost or stolen each year [7]; often the loss of a cell phone means the loss of personal data, time and enormous aggravation. In this paper we present machine-learning based algorithms by which a cell phone can discern that it may be lost, and take steps to enhance its chances of being successfully recovered. We use data collected from the Reality...
This paper describes a system that is being developed for providing services to support elderly residents in assisted living facilities. Passive RFID tags and readers are used as the basic sensor modality to distinguish people and objects. An intelligent multiagent system with a distributed topology enables local decision making without the need for a centralized server or database. Rather than use...
In this paper, we propose an unsupervised approach to separate focused main subject regions from defocused background. This algorithm first computes the blurring level using the bivariate kurtosis of all 8 times 8 DCT blocks of a photographic image with low depth of field. Then these blocks are clustered to blurry regions and sharp regions. The sharp regions are considered the main subject regions...
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