作者：
Poon, Ting-ChungOptical Image Processing Laboratory
Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University (Virginia Tech) Blacksburg VA 24061 United States
We first review a real-time three-dimensional (3-D) holographic recording technique called optical scanning holography (OSH) and discuss holographic reconstruction using spatial light modulators (SLMs). We then presen...
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Using other agents' experiences and knowledge, a learning agent may learn faster, make fewer mistakes, and create some rides for unseen situations. These benefits will be gained if the learning agents know the are...
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Using other agents' experiences and knowledge, a learning agent may learn faster, make fewer mistakes, and create some rides for unseen situations. These benefits will be gained if the learning agents know the area of expertise and the expertness values of each other. In this paper, some Q-learning agents with different skills and expertness levels cooperate in learning. The agents use some criteria to judge others information and knowledge. Four expertness criterion, certainty and entropy measures are used to assign degrees of importance to others' Q-Tables. Effects of measuring these values based on their whole Q-Table, a portion of Q-Tables that reflects their proficiencies, and the states in Q-Tables on the learning quality are studied. Simple strategy sharing and two different weighted strategy-sharing methods are used to combine the acquired knowledge from different agents.
In multiagent reinforcement learning, inter-agent credit assignment is a fundamental problem, since a single scalar reinforcement signal is the only reliable feedback that teams of learning agents receive. This proble...
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In multiagent reinforcement learning, inter-agent credit assignment is a fundamental problem, since a single scalar reinforcement signal is the only reliable feedback that teams of learning agents receive. This problem is more critical in groups of independent learners with a joint task. In this research, it is assumed that a critic agent receives the environment feedback and assigns a proper credit to each agent using some measures. Three of such measures for a team of cooperative agents with a parallel and AND-type task are introduced. These measures somehow compare the agents' knowledge. One of these criteria, called normal expertness, is a non-relative measure while two other ones (certainty and relative normal expertness) are relative measure. It is experimentally shown that relative measures work better as they contain more information for the critic agent.
The research applies space-time adaptive processing (STAP) techniques to a pseudo-circular array generated by selectively thinning a rectangular array. A hybrid approach incorporating elevation interferometry and STAP...
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ISBN:
(纸本)078037357X
The research applies space-time adaptive processing (STAP) techniques to a pseudo-circular array generated by selectively thinning a rectangular array. A hybrid approach incorporating elevation interferometry and STAP techniques is used. Results show the thinned 16-element pseudo-circular array offers significant detection performance improvement over the baseline factored time-space (FTS) technique operating on a linear array, e.g., an 8-element horizontal linear array. Results are demonstrated for cases with and without range ambiguous clutter. This performance level is achieved using a factor of M less sample support than required for full adaptivity where M represents the number of pulses within a coherent processing interval.
In this paper we propose a novel method for the construction of invariant textural features for grey scale images. The textural features are based on an averaging over the 2D Euclidean transformation group with relati...
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In many branches of industry, piled box-like objects have to be recognized, grasped and transferred. Unfortunately, existing systems only deal with the most simple configurations (i.e. neatly placed boxes) effectively...
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In this paper we present SIMBA, a content based image retrieval system performing queries based on image appearance. We consider absolute object positions irrelevant for image similarity here and therefore propose to ...
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The growth of the brain of a human embryo changes over a long period of time in the body of the mother. So it is very difficult to observe and to understand that process. Therefore, embryologists have found realistic ...
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We present a new method to visualize virtual endoscopic views. We propose to flatten the organ by the direct projection of the surface onto a set of cylinders. Two sampling strategies are presented and the introduced ...
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Textual inserts and closed captures superimposed on digital videos often contain important and exclusive information about the video contents which cannot be found in other information channels. Therefore, it is very ...
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ISBN:
(纸本)0769512631
Textual inserts and closed captures superimposed on digital videos often contain important and exclusive information about the video contents which cannot be found in other information channels. Therefore, it is very helpful to extract this information automatically and add it to a video index as generated by video archiving and retrieval systems like e.g. ADViSOR, AVAnTA, DiVA or Informedia. Owing to the fact that common OCR systems are restricted to binary images, the video frames have to be preprocessed in order to extract the textual inserts from the image in the background. In this paper we present our approach to the segmentation of textual inserts from digital videos or images, which consists of a region-growing method for color segmentation and a method of separating text regions from background based on character size and alignment constraints. A new method on segmentation refinement taking into account the results of the classification step leads to a significant enhancement of quality of the resulting binary images. The main difficulties in extracting textual inserts from video are caused by the low resolution and quality of digital video material, the high amount of image data, the very complex structured and textured background, and the unknown color size, and position of the text to be extracted from the image.
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