In order to call correct NC program automatically, real-time for corresponding online parts in the flexible manufacturing system (FMS), a new automatic recognition and classifier system based on machine vision was dev...
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ISBN:
(纸本)0819460729
In order to call correct NC program automatically, real-time for corresponding online parts in the flexible manufacturing system (FMS), a new automatic recognition and classifier system based on machine vision was developed. In the image pre-processing, to make the extraction of image edge-detection better, a new re-filter, consisting of three steps-Gauss linear smoothness filter, sharpening, Median Filter, was first introduced. Then, Canny edge detection algorithm was adopted. Moreover, comparing with the most existing classification methods, such as Nearest Neighbor, Bayesian, Off-Line computations and so on, a new classification algorithm, Two Steps Shape Classification, was proposed. Using a Radial Feature Token (RFT), which functions as the ALISA Shape Module in the Adaptive learning Image and signal Analysis (ALISA) system hierarchy. Experimental results confirm that the image processing algorithm is effective and useful for real-timely recognizing and classifying online parts in the FMS.
In this paper some applications of intelligent systems are presented. In spite of all knowledge-based technologies, which have been proposed recently, the main driving power of "intelligent" approaches is st...
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In this paper some applications of intelligent systems are presented. In spite of all knowledge-based technologies, which have been proposed recently, the main driving power of "intelligent" approaches is still (and even increasingly) huge computational power of modern information technology, that is used to process vast amounts of data. Two main technologies of intelligent systems in medicine, both based on data processing and search, are thus optimization and machinelearning. They are used for different kinds of medical problems: data mining, diagnosing, medical imaging and signalprocessing, planning and scheduling, etc. In the paper we summarize some of the most evident applications of this kind.
The patterns of ultrasonic reflected echoes from objects contain information about the geometric shape, size, orientation and the surface material properties of the reflector. Accurate estimation of the ultrasonic ech...
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The patterns of ultrasonic reflected echoes from objects contain information about the geometric shape, size, orientation and the surface material properties of the reflector. Accurate estimation of the ultrasonic echo signal pattern is essential for recognition of the target object. We propose a method to classify different objects having specific geometric shape such as cylindrical, rectangular, sphere and conical of different size and material. Here continuous wavelet transform (CWT) has been used for feature extraction. In the present work an attempt has been made to classify the pattern inherent in the features extracted through CWT of different echo signals with the help of two different machinelearning algorithms like self organizing feature map (SOFM) and support vector machine (SVM). CWT allows a time domain signal to be transformed into time frequency domain such that frequency characteristics and the location of particular features in a time series may be highlighted simultaneously. Thus it allows accurate extraction of features from the non-stationary signals like ultrasonic echo envelop. SOFM transforms the input of arbitrary dimension into a one or two dimensional discrete map subject to a topological (neighbourhood preserving) constraint. In the present work the SOFM algorithm with Kohonen's learning and SVM in regression mode has been used to classify the patterns inherent in the features extracted through CWT of different echo envelop
This paper presents a comparison among several well-known machinelearning techniques when they are used to carry out a one-session ahead prediction of page categories. We use records belonging to 18 different categor...
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A variety of techniques from statistics, signalprocessing, pattern recognition, machinelearning, and neural networks have been proposed to understand data by discovering useful categories. However, research in data ...
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In the framework of an image interpretation system for automatic cartography based on remote sensing image classification improved by a photo interpreter knowledge, we developed a system based on neural networks which...
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ISBN:
(纸本)0819423599
In the framework of an image interpretation system for automatic cartography based on remote sensing image classification improved by a photo interpreter knowledge, we developed a system based on neural networks which simultaneously produce fuzzy rules, with their linguistic approximation as well as final classification. This paper describes the succession of steps used with this aim in view. Particularly it investigates the application of mutual information criteria to simplify fuzzy rules.
This paper is about the design of a hybrid artificial neural network(ANN) system and its implementation in the Parallel Virtual machine (PVM) *** first,the PVM functions for supporting parallel applications and commun...
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This paper is about the design of a hybrid artificial neural network(ANN) system and its implementation in the Parallel Virtual machine (PVM) *** first,the PVM functions for supporting parallel applications and communications among multiple processes and multiple machines are ***,the design and construction of a hybrid ANN simulation software is *** includes user interface, control and SPMD computing *** software can be used for supporting parallel simulation of different kinds of learning algorithms and neural computing models.
This book is a collection of carefully selected works presented at the Thirdinternationalconference on Computer Vision & Image processing (CVIP 2018). The conference was organized by the Department of Computer S...
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ISBN:
(数字)9789813292918
ISBN:
(纸本)9789813292901
This book is a collection of carefully selected works presented at the Thirdinternationalconference on Computer Vision & Image processing (CVIP 2018). The conference was organized by the Department of Computer Science and Engineering of PDPM Indian Institute of Information Technology, Design & Manufacturing, Jabalpur, India during September 29 - October 01, 2018. All the papers have been rigorously reviewed by the experts from the domain. This 2 volume proceedings include technical contributions in the areas of Image/Video processing and Analysis; Image/Video Formation and Display; Image/Video Filtering, Restoration, Enhancement and Super-resolution; Image/Video Coding and Transmission; Image/Video Storage, Retrieval and Authentication; Image/Video Quality; Transform-based and Multi-resolution Image/Video Analysis; Biological and Perceptual Models for Image/Video processing; machinelearning in Image/Video Analysis; Probability and uncertainty handling for Image/Video processing; andMotion and Tracking.
This volume comprises the select proceedings of the 3rdinternationalconference on signal & Data processing - ICSDP 2023. The contents focus on the latest research and developments in the field of artificial inte...
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ISBN:
(数字)9789819795789
ISBN:
(纸本)9789819795772;9789819795802
This volume comprises the select proceedings of the 3rdinternationalconference on signal & Data processing - ICSDP 2023. The contents focus on the latest research and developments in the field of artificial intelligence & machinelearning, Internet of Things (IoT), cybernetics, advanced communication systems, VLSI embedded systems, power electronics and automation, MEMS/ nanotechnology, renewable energy, bioinformatics, data acquisition and mining, antenna & RF systems, power systems, biomedical engineering, aerospace & navigation. This volume will prove to be a valuable resource for those in academia and industry.
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