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Pattern Analysis and Machine Intelligence, IEEE Transactions on

Issue 5 • Date Sept. 1985

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Displaying Results 1 - 21 of 21
  • [Front cover]

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  • List of Contributors

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  • [Breaker page]

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  • A Knowledge-Based Approach to Design

    Page(s): 502 - 510
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    A framework is presented for constructing knowledge-based aids for design problems. In particular, we describe the organization of an interactive knowledge-based consultant for VLSI design (called VEXED¿an acronym for VLSI expert editor), and a prototype implementation of VEXED. The paper focuses on the principles underlying the design of VEXED, and on several lessons and research issues that have arisen from implementing and experimenting with this prototype. View full abstract»

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  • Strategies for Knowledge Acquisition

    Page(s): 511 - 522
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    This paper describes knowledge acquisition strategies developed in the course of handcrafting a diagnostic system and reports on their consequent implementation in MORE, an automated knowledge acquisition system. We describe MORE in some detail, focusing on its representation of domain knowledge, rule generation capabilities, and interviewing techniques. MORE's approach is shown to embody methods which may prove fruitful to the development of knowledge acquisition systems in other domains. View full abstract»

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  • Gradualness Facilitates Knowledge Refinement

    Page(s): 523 - 530
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    To facilitate knowledge refinement, a system should be designed so that small changes in the knowledge correspond to small changes in the function or performance of the system. Two sets of experiments show the value of small, heuristically guided changes in a weighted rule base. In the first set, the ordering among numbers (reflecting certainties) makes their manipulation more straightforward than the manipulation of relationships. A simple credit assignment and weight adjustment strategy for improving numbers in a weighted, rule-based expert system is presented. In the second set, the rearrangement of predicates benefits from additional knowledge about the ``ordering'' among predicates. A third set of experiments indicates the importance of the proper level of granularity when augmenting a knowledge base. Augmentation of one knowledge base by analogical reasoning from another knowledge base did not work with only binary relationships, but did succeed with ternary relationships. To obtain a small improvement in the knowledge base, a substantial amount of structure had to be treated as a unit. View full abstract»

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  • Representation of Activity Knowledge for Project Management

    Page(s): 531 - 552
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    Representation of activity knowledge is important to any application which must reason about activities such as new product management, factory scheduling, robot control, vehicle control, software engineering, and air traffic control. This paper provides an integration of the underlying theories needed for modeling activities. Using the domain of large computer design projects as an example, the semantics of activity modeling is described. While the past research in knowledge representation has discovered most of the underlying concepts, our attempt is toward their integration. This includes the epistemological concepts for erecting the required knowledge structure; the concepts of activity, state, goal, and manifestation for the adequate description of the plan and the progress; and the concepts of time and causality to infer the progression among the activities. We also address the issues which arise due to the integration of aggregation, time, and causality among activities and states. View full abstract»

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  • A General Expert System Design for Diagnostic Problem Solving

    Page(s): 553 - 560
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    Existing expert systems have a high percentage agreement with experts in a particular field in many situations. However, in many ways their overall behavior is not like that of a human expert. These areas include the inability to give flexible, functional explanations of their reasoning processes, and the failure to degrade gracefully when dealing with problems at the periphery of their knowledge. These two important shortcomings can be improved when the right knowledge is available to the system. This paper presents an expert system design, called the integrated diagnostic model (IDM), that integrates two sources of knowledge, a shallow, reasoning-oriented, experiential knowledge base and a deep, functionally oriented, physical knowledge base. To demonstrate the IDM's usefulness in the problem area of diagnosis and repair, an implementation in the mechanical domain is described. View full abstract»

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  • R1-Soar: An Experiment in Knowledge-Intensive Programming in a Problem-Solving Architecture

    Page(s): 561 - 569
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    This paper presents an experiment in knowledge-intensive programming within a general problem-solving production-system architecture called Soar. In Soar, knowledge is encoded within a set of problem spaces, which yields a system capable of reasoning from first principles. Expertise consists of additional rules that guide complex problem-space searches and substitute for expensive problem-space operators. The resulting system uses both knowledge and search when relevant. Expertise knowledge is acquired either by having it programmed, or by a chunking mechanism that automatically learns new rules reflecting the results implicit in the knowledge of the problem spaces. The approach is demonstrated on the computer-system configuration task, the task performed by the expert system R1. View full abstract»

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  • Rule-Based Interpretation of Aerial Imagery

    Page(s): 570 - 585
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    In this paper, we describe the organization of a rule-based system, SPAM, that uses map and domain-specific knowledge to interpret airport scenes. This research investigates the use of a rule-based system for the control of image processing and interpretation of results with respect to a world model, as well as the representation of the world model within an image/map database. We present results on the interpretation of a high-resolution airport scene wvhere the image segmentation has been performed by a human, and by a region-based image segmentation program. The results of the system's analysis is characterized by the labeling of individual regions in the image and the collection of these regions into consistent interpretations of the major components of an airport model. These interpretations are ranked on the basis of their overall spatial and structural consistency. Some evaluations based on the results from three evolutionary versions of SPAM are presented. View full abstract»

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  • An Approach to Expert Control of Interactive Software Systems

    Page(s): 586 - 591
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    Expert problem-solving strategies in many domains require the use of detailed mathematical techniques coupled with experiential knowledge about how and when to use the appropriate techniques. In many of these domains, such techniques are made available to experts in large software packages. In attempting to build expert systems for these domains, we wish to make use of these packages, and are therefore faced with an important problem: how to integrate the existing software, and knowledge about its use, into a practical expert system. The expert knowledge is used, in dynamic selection and interpretation of appropriate programs and parameters, to reach a successful goal in the problem solving. We describe the framework of a hybrid expert system for representing problem-solving knowledge in these domains. This hybrid system may be characterized as consisting of a production system and mathematical methods. The software package is reorganized as necessary to map it into the mathematical-method representation of a hybrid system. This approach has evolved out of an effort to build an expert system for performing well-log analysis, ELAS (expert log analysis system). View full abstract»

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  • Conceptual Clustering in Knowledge Organization

    Page(s): 592 - 598
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    Knowledge organization is a very important step in building an expert system. The problem is how to organize knowledge into a conceptual structure and thus make it complete, concise, and consistent. In this paper, concepts used in knowledge description are divided into tangible ones and intermediate ones depending on whether or not they appear in the input or the output of the system. Intermediate concepts and their relationships with tangible concepts are subjected to changes. A distance measure for rules and an algorithm for conceptual clustering are described. New intermediate concepts are generated using this algorithm. A few new concepts may replace a large number of old relationships and also generate new rules for the system. An experiment on traditional Chinese medicine shows that the proposed method produces results similar to those generated by experts. View full abstract»

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  • Entropy and Distance of Random Graphs with Application to Structural Pattern Recognition

    Page(s): 599 - 609
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    The notion of a random graph is formally defined. It deals with both the probabilistic and the structural aspects of relational data. By interpreting an ensemble of attributed graphs as the outcomes of a random graph, we can use its lower order distribution to characterize the ensemble. To reflect the variability of a random graph, Shannon's entropy measure is used. To synthesize an ensemble of attributed graphs into the distribution of a random graph (or a set of distributions), we propose a distance measure between random graphs based on the minimum change of entropy before and after their merging. When the ensemble contains more than one class of pattern graphs, the synthesis process yields distributions corresponding to various classes. This process corresponds to unsupervised learning in pattern classification. Using the maximum likelihood rule and the probability computed for the pattern graph, based on its matching with the random graph distributions of different classes, we can classify the pattern graph to a class. View full abstract»

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  • Geometric Reconstruction of Buried Heat Sources from a Surface Thermogram

    Page(s): 610 - 616
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    Attempts to reconstruct the spatial location, size, and form of buried heat sources from the measured pattern of thermograms are, in general, prohibited by the lack of a priori information about the thermal (flow) model and the source structure. In this paper, a method is introduced based on geometric reconstruction of a buried heat source configuration. This configuration must contain point sources and/or sharp edges and be confined to a plane region parallel to the surface. The medium, in which the heat source is embedded, is assumed to be homogeneous, isotropic, and of large size compared to the size of the source and to its depth below the surface. The heat flux from the surface to the ambient is assumed to follow the Newtonian cooling law. The spatial density distribution of the flux can be described by a Green function with coefficients determined by the depth of the source plane. It is possible to approximate a corresponding inverse mapping algorithm (reconstruction filter) for each source plane depth, with only one (depth) scaling parameter. The density distribution of the source structure is optimally deblurred when the reconstruction filter's scaling parameter matches the actual depth of the source plane below the surface. In the reconstruction procedure, this reconstruction filter is consecutively applied for several values of the scaling parameter. The so-called ``deblurring quality'' of the point or edge information is utilized to decide which scaling parameter achieves the sharpest image. This procedure resembles the focusing of a lens. View full abstract»

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  • Relaxation Matching Techniques-A Comparison

    Page(s): 617 - 623
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    Many different relaxation schemes have been proposed for image analysis tasks. We have developed a general matching procedure for comparing semantic network descriptions of images, and we have implemented a variety of relaxation techniques. An automatic segmentation and description system is used to produce the image representations so that the matching procedures must cope with variations in feature values, missing objects, and possible multiple matches. This environment is used to test different relaxation matching schemes under a variety of conditions. The best performance (of those we compared), in terms of the number of iterations and the number of errors, is for the gradient-based optimization approach of Faugeras and Price. The related optimization approach of Hummel and Zucker performed almost as well, with differences primarily in difficult matches (i.e., where much of the evidence is against the match, for instance, poor segmentations). The product combination rule proposed by Peleg was extremely fast, indeed, too fast to work when global context is needed. The classical Rosenfeld, Hummel, and Zucker method is included for historical comparisons and performed only adequately, producing fewer correct matches and taking more iterations. View full abstract»

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  • Distributed Computing for Vision: Architecture and a Benchmark Test

    Page(s): 623 - 626
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    Computer vision algorithms are notorious for their computational expense. Distributed vision, the use of more than one processor, can decrease computation costs and speed up algorithms. There are various ways to do this, ranging from parallelism at the sensor level to true multiprocessor systems. This correspondence first describes a system of the latter type: a system of microprocessors on a high-speed bus. A canonical vision task, locating a number of objects and measuring certain two-dimensional features of those objects, serves as a benchmark test for the system. An algorithm for this task is presented. Performance measures are compared from implementations on the distributed system, a Vax 11/750, and a Vax 11/780. Results indicate that three microprocessors outperform a Vax 11/780 at this task. Finally, other more interesting distributed algorithms are briefly discussed. View full abstract»

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  • List of Reviewers

    Page(s): 627
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  • Content Announcement

    Page(s): 628
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  • List of Contributors

    Page(s): nil2
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  • [Front cover]

    Page(s): c2
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Aims & Scope

The IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) is published monthly. Its editorial board strives to present most important research results in areas within TPAMI's scope.

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Meet Our Editors

Editor-in-Chief
David A. Forsyth
University of Illinois