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1.
We present a fast video retrieval system with three novel characteristics. First, it exploits the methods of machine learning to construct automatically a hierarchy of small subsets of features that are progressively more useful for indexing. These subsets are induced by a new heuristic method called Sort-Merge feature selection, which exploits a novel combination of Fastmap for dimensionality reduction and Mahalanobis distance for likelihood determination. Second, because these induced feature sets form a hierarchy with increasing classification accuracy, video segments can be segmented and categorized simultaneously in a coarse-fine manner that efficiently and progressively detects and refines their temporal boundaries. Third, the feature set hierarchy enables an efficient implementation of query systems by the approach of lazy evaluation, in which new queries are used to refine the retrieval index in real-time. We analyze the performance of these methods, and demonstrate them in the domain of a 75-min instructional video and a 30-min baseball video.  相似文献
2.
Logic simulation is used extensively in the design of digital systems for the purpose of studying the behaviour of circuits under various conditions and for verifying the required performance of circuits. There is considerable interest in methods which reduce the simulation time during the design process. In this paper, we investigate how this can be achieved by simulating the action of logic circuits using a network of loosely coupled processors. Circuits modelled as directed graphs comprising clocked sequential components and (unclocked) arbitrary combinational logic gates can be partitioned into separate tasks each consisting of a sequential component with an associated network of combinational components. We present cost functions for evaluating a task subject to probabilistic assumptions about the functioning of the circuits. The circuit evaluation method used in the simulation process is significant. We apply lazy evaluation, a demand-driven evaluation strategy in which signals in the circuit are evaluated on a ‘need to do' basis, resulting in a considerable saving in circuit simulation time. We achieve distributed logic simulation using a network of workstations and show from experimental results that by using such a configuration, we essentially obtain a single computation engine which can be used to obtain speedups in circuit simulation when compared with uniprocessor simulation systems. Interprocess communications between tasks on different workstations proceed via remote procedure calls while local communications between tasks take place via shared memory. The method of partitioning used in the circuit model ensures that communications between tasks take place only at defined times in the simulation sequence.  相似文献
3.
This paper examines the transformation of call-by-need terms into continuation-passing style (CPS). It begins by presenting a simple transformation of call-by-need terms into program graphs and a reducer for such graphs. From this, an informal derivation is carried out, resulting in a translation from terms into self-reducing program graphs, where the graphs are represented as CPS terms involving storage operations. Though informal, the derivation proceeds in simple steps, and the resulting translation is taken to be our canonical CPS transformation for call-by-need terms.In order to define the CPS transformation more formally, two alternative presentations are given. The first takes the form of a continuation semantics for the call-by-need language. The second presentation follows Danvy and Hatcliff's two-stage decomposition of the call-by-name CPS transformation, resulting in a similar two-stage CPS transformation for call-by-need.Finally, a number of practical matters are considered, including an improvement to eliminate the so-called administrative redexes, as well as to avoid unnecessary memoization and take advantage of strictness information. These improvements make it feasible to consider potential applications in compilers for call-by-need programming languages.Supported in part by the National Science Foundation under PYI grant #CCR-9057567, with matching funds from Bell Northern Research.Supported by an AT&T Ph.D. scholarship.  相似文献
4.
A new method of searching large dictionaries given uncertain inputs is described, based on the lazy evaluation of a syntactic neural network (SNN). The new method is shown to significantly outperform a conventional trie-based method for large dictionaries (e.g. in excess of 100,000 entries). Results are presented for the problem of recognising UK postcodes using dictionary sizes of up to 1 million entries. Most significantly, it is demonstrated that the SNN actually gets faster as more data is loaded into it.  相似文献
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6.
*1 Constraint Satisfaction Problems (CSPs)17) are an effective framework for modeling a variety of real life applications and many techniques have been proposed for solving them efficiently. CSPs are based on the assumption that all constrained data (values in variable domains) are available at the beginning of the computation. However, many non-toy problems derive their parameters from an external environment. Data retrieval can be a hard task, because data can come from a third-party system that has to convert information encoded with signals (derived from sensors) into symbolic information (exploitable by a CSP solver). Also, data can be provided by the user or have to be queried to a database. For this purpose, we introduce an extension of the widely used CSP model, called Interactive Constraint Satisfaction Problem (ICSP) model. The variable domain values can be acquired when needed during the resolution process by means of Interactive Constraints, which retrieve (possibly consistent) information. A general framework for constraint propagation algorithms is proposed which is parametric in the number of acquisitions performed at each step. Experimental results show the effectiveness of the proposed approach. Some applications which can benefit from the proposed solution are also discussed. This paper is an extended and revised version of the paper presented at IJCAI’99 (Stockholm, August 1999)4). Paola Mello, Ph.D.: She received her degree in Electronic Engineering from University of Bologna, Italy, in 1982 and her Ph.D. degree in Computer Science in 1989. Since 1994 she is full Professor. She is enrolled, at present, at the Faculty of Engineering of the University of Bologna where she teaches Artificial Intelligence. Her research activity focuses around: programming languages, with particular reference to logic languages and their extensions towards modular and object-oriented programming; artificial intelligence; knowledge representation; expert systems. Her research has covered implementation, application and theoretical aspects and is presented in several national and international publications. She took part to several national (Progetti Finalizzati e MURST) and international (UE) research projects in the context of computational logic. Michela Milano, Ph.D.: She is a Researcher in the Department of Electronics, Computer Science and Systems at the University of Bologna. From the same University she obtained her master degree in 1994 and her Ph.D. in 1998. In 1999 she had a post-doc position at the University of Ferrara. Her research focuses on Artificial Intelligence, Constraint Satisfaction and Constraint Programming. In particular, she worked on using and extending the constraint-based paradigm for solving real-life problems such as scheduling, routing, object recognition and planning. She has served on the program committees of several international conferences in the area of Constraint Satisfaction and Programming, and she has served as referee in several related international journals. Marco Gavanelli: He is currently a Ph.D. Student in the Department of Engineering at the University of Ferrara, Italy. He graduated in Computer Science Engineering in 1998 at the University of Bologna, Italy. His research interest include Artificial Intelligence, Constraint Logic Programming, Constraint Satisfaction and visual recognition. He is a member of ALP (the Association for Logic Programming) and AI*IA (the Italian Association for Artificial Intelligence). Evelina Lamma, Ph.D.: She got her degree in Electrical Engineering at the University of Bologna in 1985, and her Ph.D. in Computer Science in 1990. Her research activity centers on logic programming languages, Artificial Intelligence and software engineering. She was co-organizers of the 3rd International Workshop on Extensions of Logic Programming ELP92, held in Bologna in February 1992, and of the 6th Italian Congress on Artificial Intelligence, held in Bologna in September 1999. She is a member of the Executive Committee of the Italian Association for Artificial Intelligence (AI*IA). Currently, she is Full Professor at the University of Ferrara, where she teaches Artificial Intelligence and Fondations of Computer Science. Massimo Piccardi, Ph.D.: He graduated in electronic engineering at the University of Bologna, Italy, in 1991, where he received a Ph.D. in computer science and computer engineering in 1995. He currently an assistant professor of computer science with the Faculty of Engineering at the University of Ferrara, Italy, where he teaches courses on computer architecture and microprocessor systems. Massimo Piccardi participated in several research projects in the area of computer vision and pattern recognition. His research interests include architectures, algorithms and benchmarks for computer vision and pattern recognition. He is author of more than forty papers on international scientific journals and conference proceedings. Dr. Piccardi is a member of the IEEE, the IEEE Computer Society, and the International Association for Pattern Recognition — Italian Chapter. Rita Cucchiara, Ph.D.: She is an associate professor of computer science at the Faculty of Engineering at the University of Modena and Reggio Emilia, Italy, where she teaches courses on computer architecture and computer vision. She graduated in electronic engineering at the University of Bologna, Italy, in 1989 and she received a Ph.D. in electronic engineering and computer science from the same university in 1993. From 1993 to 1998 she been an assistant professor of computer science with the University of Ferrara, Italy. She participated in many research projects, including a SIMD parallel system for vision in the context of an Italian advanced research program in robotics, funded by CNR (the Italian National Research Council). Her research interests include architecture and algorithms for computer vision and multimedia systems. She is author of several papers on scientific journals and conference proceedings. She is member of the IEEE, the IEEE Computer Society, and the International Association for Pattern Recognition — Italian Chapter.  相似文献
7.
本文给出高阶函数式语言到Prolog语言的一种转换技术.其中主要用到抽象闭包分析、Lambda提升、顺序化以及Prolog中的Cal技术.本文的研究重点在于高阶性的处理上.  相似文献
8.
The debugging of fully lazy functional programs can require searching a very large reduction-history space containing many delayed computations. A debugger should provide a means to obtain a source level representation of the computation, which can be large, and a means to select the appropriate part of the computation to investigate, which can be difficult. A method is presented to compile functional programs to combinator code such that a source-like representation of any part of a computation graph can be efficiently reconstructed at run-time. Other less efficient methods require excessive compile-time guidance as to the specific part of the computation to be investigated. Reconstruction, forward reduction, and a history-rollback mechanism combine to make the entire source-like reduction-history space dynamically available at run-time. The deferring of debugging decisions until run-time is called lazy dubugging. Once the computation-sequence is meaningfully and efficiently available, the problem of debugging becomes that of localizing the search for the error. Some searching issues are discussed with respect to graph browsing and user-interface design. The method shows promise as a programmer tool to debug programs and to informally reason about the time and space behavior of fully lazy functional programs, a nonintuitive process due to the subtleness of sharing and delayed computations.  相似文献
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10.
We present a generic C++ design to perform exact geometric computations efficiently using lazy evaluations. Exact geometric computations are critical for the robustness of geometric algorithms. Their efficiency is also important for many applications, hence the need for delaying the costly exact computations at run time until they are actually needed, if at all. Our approach is generic and extensible in the sense that it is possible to make it a library that users can apply to their own geometric objects and primitives. It involves techniques such as generic functor-adaptors, static and dynamic polymorphism, reference counting for the management of directed acyclic graphs, and exception handling for triggering exact computations when needed. It also relies on multi-precision arithmetic as well as interval arithmetic. We apply our approach to the whole geometry kernel of Cgal.  相似文献
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