The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.

Classification and regression trees

Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

Data Mining - Concepts and Techniques.

The primary goal of pattern recognition is supervised or unsupervised classification. Among the various frameworks in which pattern recognition has been traditionally formulated, the statistical approach has been most intensively studied and used in practice. More recently, neural network techniques and methods imported from statistical learning theory have been receiving increasing attention. The design of a recognition system requires careful attention to the following issues: definition of pattern classes, sensing environment, pattern representation, feature extraction and selection, cluster analysis, classifier design and learning, selection of training and test samples, and performance evaluation. In spite of almost 50 years of research and development in this field, the general problem of recognizing complex patterns with arbitrary orientation, location, and scale remains unsolved. New and emerging applications, such as data mining, web searching, retrieval of multimedia data, face recognition, and cursive handwriting recognition, require robust and efficient pattern recognition techniques. The objective of this review paper is to summarize and compare some of the well-known methods used in various stages of a pattern recognition system and identify research topics and applications which are at the forefront of this exciting and challenging field.

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Statistical pattern recognition: a review

Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms. The treatment is centered on robot motion planning but integrates material on planning in discrete spaces. A major part of the book is devoted to planning under uncertainty, including decision theory, Markov decision processes, and information spaces, which are the “configuration spaces” of all sensor-based planning problems. The last part of the book delves into planning under differential constraints that arise when automating the motions of virtually any mechanical system. Developed from courses taught by the author, the book is intended for students, engineers, and researchers in robotics, artificial intelligence, and control theory as well as computer graphics, algorithms, and computational biology.

Planning Algorithms: Introductory Material

This paper addresses the problem of direct image and video manipulation in compressed domain The capability to perform such manipulations has become attractive in recent years, as more and more visual information is being captured, stored, and moved in compressed form Our solution to direct manipulation of compressed images and video is based on a set of block-level transforms, called the inner block transforms (IBTs) Each IBT requires a minimal computation effort in compressed domain to yield a regular geometric transformation on an image block The paper shows how the IBTs can be used to perform many image and video manipulations This is done by describing the application of IBTs to image subtitling, shearing, and arbitrary angle rotation The paper also discusses the application of IBT to M-JPEG and MPEG video The benefits of the proposed direct compressed domain manipulation approach include faster speed, preservation of image quality, and less computing resources

Block-based manipulations on transform-compressed images and videos

Walsh descriptors for polygonal curves

This paper presents an approach to evaluate the quality of handwritten letters based on the set of features that are used by human handwriting experts. The use of these attributes allows very intuitive interpretation of the results and as a consequence provides solid foundation for feedback to the end user of the system. A combination of an artificial neural network and an expert system is used to evaluate and grade each handwritten letter, as well as to provide feedback to the student. The application of such a system would be in the educational field for handwriting teaching and repair.

Handwriting Quality Evaluation

The paper presents a modularization method for the design of MPEG decoding software. Compared to the traditional MPEG decoder architecture, the architecture obtained from the modularization method can effectively improve the flexibility and reusability of MPEG decoding software without affecting the speed performance. Using this design approach, the paper presents MPEG Developing Classes (MDC), a software tool for developing MPEG video applications. The feedback from users of MDC shows that MDC is flexible in use and easy to understand. It allows users to develop their specific decoders without going into details of MPEG.

MDC: a software tool for developing MPEG applications

Software Project Management (SPM) is one of the primary factors to software success or failure. Software projects often fail because the mangers do not know true project status. Software project planning can be one of the most critical activities in the SPM process. Without a realistic and objective software project plan, the software development process cannot be managed in an effective way. This paper presents a metric-based multi-agent system, Software Project Planning Associate (SPPA), to assist managers in understanding and visualizing SPM process defined in a software project plan. SPPA consists of Intelligent Agents developed in the Java programming language and JESS (Java Expert System Shell) to assist a software project manager in objectively initializing a software project plan, refining/improving a plan, organizing, staffing, scheduling, measuring, visualizing, controlling, tracking, predicting, and data collecting. The resources, tasks, schedules, and milestones of the software project are described in a generic metric-based software project plan. As software development process evolves, metrics are unobtrusively gathered and compliance to the plan is reported by intelligent agents. Software process effectiveness predictions are made and recommendations are dynamically reported by multi intelligent agents suggesting the software development that should be executed to best comply with the software project plan.

https://www2.computer.org/portal/web/csdl/doi/10.1109/ICIS.2009.105

Ishwar K. Sethi

Papers

Block-based manipulations on transform-compressed images and videos

Walsh descriptors for polygonal curves

Handwriting Quality Evaluation

MDC: a software tool for developing MPEG applications

A Metric-Based Multi-Agent System for Software Project Management