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This paper presents a new approach to the problem of semantic segmentation of digital images. We aim to improve the performance of some state-of-the-art approaches for the task. We exploit a new version of texton feature [28], which can encode image texture and object layout for learning a robust classifier. We propose to use a genetic algorithm for the learning parameters of weak classifiers in a...
The improvement of energy efficiency in wireless cellular networks has become a popular topic in recent years due to its positive effects on the environment and economical benefits for network operators. An effective way to improve energy efficiency is to deploy energy-efficient base stations and turn as many base stations off as possible. In this paper, we consider an LTE network composed by the...
A new method for reconfigurable modular robot on configuration auto-generation, optimization and evaluation was proposed in this paper. On the basis of assign and design of the module, a new descriptive method of configuration-CCM was proposed, and it can describe the configuration directly and completely which needed to satisfy the assembly requirement. Genetic-simulated annealing algorithm has been...
Gabor Wavelets are widely used to extract facial features since they are robust against illumination and pose changes. Due to the limitation in computational power, the common practice is to down-sample the face image to reduce number of Gabor features generated. As not all of the generated Gabor features are necessary, the main objective of this paper is to develop an efficient removal scheme of...
This work presents a framework that combines the concept of Fuzzy Quantile Inference (FQI) with Genetic Programming (GP) in order to accurately classify real natural 3d human Motion Capture data. FQI is a generalization of Fuzzy Gaussian Inference. It builds Fuzzy Membership Functions that map to hidden Probability Distributions underlying human motions, providing a suitable modelling paradigm for...
Automatic recognition of skin symptom plays an importance role in the skin diagnosis and treatment. Feature selection is to increase the classification performance of skin symptom. In this paper, the effects of feature selection on the classification of 4-class skin symptoms (chloasma, blackhead, freckled and comedone) are analyzed. Support vector machine (SVM) is employed to construct classifier,...
Feature selection, structure determination and connection weights training are three key tasks for the classification problem based on neural network. Traditional feature selection methods with neural networks neglect the fact that these three tasks are interdependent and make a joint contribution to the performance of neural network, which often results in an irrational network structure and unsatisfying...
This paper proposes a new technique of edge detection for inspecting edge and perfection of soldering joint in the pre-amplifier circuit, which is an important part in hard disk drive. Summation of error between the actual value and the measured value from the designed system of several data sets is formulated as the objective function. Genetic algorithm (GA) is adopted to find the optimal filter...
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