A Study on Application of Artificial Neural Network and Genetic Algorithm in Pattern Recognition
نویسنده
چکیده
Binapani Sethi MTech (ECE) Konark Institute of Science & Technology, Bhubaneswar, Odisha [email protected] Abstract Image processing is an emerging field and lots of research had been performed for the past few years. Image processing has various techniques which are image segmentation, enhancement, feature extraction, classification, restoration, image generation etc. pattern recognition is an important part of image processing system. The aim of this paper is to study the use of artificial neural network and genetic algorithm in pattern recognition. Artificial neural network helps in training process where as the selection of various parameters for pattern recognition can be done in an optimized way by the genetic algorithm.
منابع مشابه
Pattern Recognition in Control Chart Using Neural Network based on a New Statistical Feature
Today for the expedition of the identification and timely correction of process deviations, it is necessary to use advanced techniques to minimize the costs of production of defective products. In this way control charts as one of the important tools for the statistical process control in combination with modern tools such as artificial neural networks have been used. The artificial neural netw...
متن کاملLIQUEFACTION POTENTIAL ASSESSMENT USING MULTILAYER ARTIFICIAL NEURAL NETWORK
In this study, a low-cost, rapid and qualitative evaluation procedure is presented using dynamic pattern recognition analysis to assess liquefaction potential which is useful in the planning, zoning, general hazard assessment, and delineation of areas, Dynamic pattern recognition using neural networks is generally considered to be an effective tool for assessing of hazard potential on the b...
متن کاملApplication of artificial neural network and genetic algorithm to modelling the groundwater inflow to an advancing open pit mine
In this study, a hybrid intelligent model has been designed to predict groundwater inflow to a mine pit during its advance. Novel hybrid method coupling artificial neural network (ANN) with genetic algorithm (GA) called ANN-GA, was utilised. Ratios of pit depth to aquifer thickness, pit bottom radius to its top radius, inverse of pit advance time and the hydraulic head (HH) in the observation w...
متن کاملThe Predictability Power of Neural Network and Genetic Algorithm from Fiems’ Financial crisis
Organizations expose to financial risk that can lead to bankruptcy and loss of business is increased nowadays. This may leads to discontinuity in operations, increased legal fees, administrative costs and other indirect costs. Accordingly, the purpose of this study was to predict the financial crisis of Tehran Stock Exchange using neural network and genetic algorithm. This research is descripti...
متن کاملDiagnosis of Breast Cancer using a Combination of Genetic Algorithm and Artificial Neural Network in Medical Infrared Thermal Imaging
Introduction This study is an effort to diagnose breast cancer by processing the quantitative and qualitative information obtained from medical infrared imaging. The medical infrared imaging is free from any harmful radiation and it is one of the best advantages of the proposed method. By analyzing this information, the best diagnostic parameters among the available parameters are selected and ...
متن کاملApplication of Artificial Neural Network and Genetic Algorithm for Predicting three Important Parameters in Bakery Industries
Farinograph is the most frequently used equipment for empirical rheological measurements of dough. It’suseful to illustrate quality of flour, behavior of dough during mechanical handling and texturalcharacteristics of finished products. The percentage of water absorption and the development time of doughare the most important parameters of farinography for bakery industries during production. H...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2012