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The non-linear, unstable system of the two wheeled self-balancing robot has made it a popular research subject within the past decade. This paper outlines the design of a two wheeled robot with self balancing control systems using Reinforcement Learning. The BeagleBone Black platform was used to design the two wheeled robot. Along with the motor, the robot was also equipped with an accelerometer and...
In a complex environment radar plot is often changing dramatically, non-uniform, discontinuous, uncertain and containing lots of false alarms. It is difficult for tracking system to form tracks in such complex environment. Traditional track formation methods can not accurately determine the size of track initiation gate and select specific initiation criteria. In this paper, an intelligent information...
In this paper, we apply the principal component analysis (PCA) to extract significant image features and then incorporated them with the proposed two-phase fuzzy adaptive resonance theory neural network (Fuzzy-ART) for image content classification to overcome the gap between the low level features and high level semantic concepts. In general, Fuzzy-ART is an unsupervised clustering. Meanwhile, the...
We consider the problem of estimating the physical locations of nodes in an indoor wireless network since knowing the physical locations of the nodes is important to many tasks of a wireless network such as network management, event detection, location-based service, and routing. A hierarchical support vector machines (H-SVM) scheme is proposed with the following advantages. First, H-SVM offers an...
Abstract-Analyzing the contents of an image and retrieving corresponding semantics are important in semantic-based image retrieval system. In this paper, we apply the independent component analysis (ICA) to extract significant image features and then incorporated it with the proposed Two-phase Fuzzy Adaptive Resonance Theory Neural Network (Fuzzy-ARTNN) for image content classification. In general,...
Extracting complete figures from videos with complicated environments is difficult. A new figure extraction and synthesis system with capability of extracting figures from consecutive frames in a messy environment is proposed in this paper. A figure template is constructed based on the face detection results and some image processing techniques. Figural and non-figural features are extracted from...
The capability of robotic emotion recognition is an important factor for human-robot interaction. In order to facilitate a robot to function in daily live environments, a emotion recognition system needs to accommodate itself to various persons. In this paper, an emotion recognition system that can adapt to new facial data is proposed. The main idea of the proposed learning algorithm is to adjust...
The objective of this paper is to develop a complete solution for recurrent nasal papilloma (RNP) detection. Recently, the gadolinium-enhanced dynamic magnetic resonance image (MRI) has been developed and widely used in clinical diagnosis of recurrent nasal papilloma. Owing to the response of RNP regions in gadolinium-enhanced magnetic resonance images is different from the response of normal tissues,...
The EM algorithm is one of the most popular statistical learning algorithms. It is a method for parameter estimation in various problems involving missing data. However, it is a batch learning method and often requires significant computational resources. So we need to develop more elaborate methods to adapt the databases with a large number of records or large dimensionality. In this paper, we present...
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