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This paper presents an adaptive mixtures-based method for segmenting moving objects in surveillance video with pixel-wise accuracy. The proposed method employs a Gaussian mixture model (GMM) to represent the intensity change of a pixel over time. The GMM consists of a background component and one or more moving object component(s). The parameters of the GMM are estimated by using an adaptive algorithm...
We propose a new method for accurate detection of architectural distortion that is a typical sign of breast cancer lesions in mammograms and necessary to be detected and diagnosed properly at an early stage for improvement of the survival rate of patients. An essential core of the proposed method is to efficiently extract a new general feature of the architectural distortions whose lesional intensities...
This paper proposes a three-dimensional (3-D) phase correlation-based rigid volume registration method for estimation of the lung tumor motion in four-dimensional (4-D) computed tomography (CT). In the lung cancer radiotherapy treatment, the 4-D thorax CT has been used to observe the spatiotemporal tumor motion with the patient's respiration. In the proposed method, the respiration-induced lung tumor...
The consensus speed of leader-following multi-agent systems with double-integrator dynamics is considered. Based on the feature of leader-following multi-agent system with fixed undirected topology, an improved algorithm is proposed, which is more effective than the traditional algorithm. The maximum consensus speed (maximum convergence speed) of the improved algorithm is also achieved and it is compared...
Traditional reinforcement learning algorithm can only solve the learning problem of the intelligent agent with discrete state space and discrete action space. This paper studies the coordination of multiple intelligent agents in a complicated dynamic environment with uncertainty. A coordination model based on the fuzzy Q-learning technique is suggested. This model uses fuzzy logic to generalize the...
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