The Experts below are selected from a list of 444 Experts worldwide ranked by ideXlab platform

Steve Chien - One of the best experts on this subject based on the ideXlab platform.

  • Automating Image processing for scientific data analysis of a large Image database
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996
    Co-Authors: Steve Chien, H.b. Mortensen
    Abstract:

    Describes the Multimission VICAR Planner (MVP): an AI planning system which uses knowledge about Image processing steps and their requirements to construct Executable Image processing scripts to support high-level science requests made to the Jet Propulsion Laboratory (JPL) Multimission Image Processing Subsystem (MIPS). This article describes a general AI planning approach to automation and application of the approach to a specific area of Image processing for planetary science applications involving radiometric correction, color triplet reconstruction, and mosaicing in which the MVP system significantly reduces the amount of effort required by Image processing experts to fill a typical request.

  • Integrated Planning for Automated Image Processing
    1995
    Co-Authors: Steve Chien, Helen Mortensen, Christine Ying, Shouyi Hsiao
    Abstract:

    The Multimission VICAR Planner (MVP) system is an AI planning system which constructs Executable Image processing programs to support Operational Science Analysis (OSA) re~j uests made to the Jet Propulsion Laboratory PL) Multimission Image Processing Subsystem (MIPS). MVP accepts as input: Image files and a high-level specification of desired corrections, enhancements, output properties (such as for mosaics). MVP then derives: unspecified but required processing steps, relevant Image processing library programs, and appropriate parameter settings for such programs - constructing an Executable Image processing program to fill the Image processing request. MVP is currently available to analysts to fill requests and reduces the effort to fill radiometric correction, color triplet reconstruction, and mosaicking tasks by over an order of magnitude.

  • Automated synthesis of Image processing procedures using AI planning techniques
    1994
    Co-Authors: Steve Chien, Helen Mortensen
    Abstract:

    This paper describes the Multimission VICAR (Video Image Communication and Retrieval) Planner (MVP) (Chien 1994) system, which uses artificial intelligence planning techniques (Iwasaki & Friedland, 1985, Pemberthy & Weld, 1992, Stefik, 1981) to automatically construct Executable complex Image processing procedures (using models of the smaller constituent Image processing subprograms) in response to Image processing requests made to the JPL Multimission Image Processing Laboratory (MIPL). The MVP system allows the user to specify the Image processing requirements in terms of the various types of correction required. Given this information, MVP derives unspecified required processing steps and determines appropriate Image processing programs and parameters to achieve the specified Image processing goals. This information is output as an Executable Image processing program which can then be executed to fill the processing request.

  • Using AI Planning Techniques to Automatically Generate Image Processing Procedures: A Preliminary Report
    1994
    Co-Authors: Steve Chien
    Abstract:

    This paper describes work on the Multimission VICAR Planner (MVP) system to automatically construct Executable Image processing procedures for custom Image processing requests for the JPL Multimission Image Processing Lab (MIPL). This paper focuses on two issues. First, large search spaces caused by complex plans required the use of hand encoded control information. In order to address this in a manner similar to that used by human experts, MVP uses a decomposition-based planner to implement hierarchical/skeletal planning at the higher level and then uses a classical operator based planner to solve subproblems in contexts defined by the highlevel decomposition. Second, the Image processing domain is characterized by large amounts of search to find the correct program options for Images (e.g. operator effects), rather than search among different programs (e.g. planning operators) and many of these program options are incompatible (i.e. certain combinations cannot be used). MVP represents these interactions by using codesignation constraints to specify program options for operators and allowing these constraints to occur in operator preconditions allowing MVP to search the program option space efficiently while handling negative interactions between program options.

  • ICIP (3) - Automated synthesis of Image processing procedures for a large-scale Image database
    Proceedings of 1st International Conference on Image Processing, 1
    Co-Authors: Steve Chien
    Abstract:

    This paper describes the Multimission VICAR Planner (MVP) system, which uses models of the Image processing programs to automatically construct Executable Image processing procedures to fill science requests made to the JPL Multimission Image Processing Laboratory (MIPL). The MVP system allows the user to specify the Image processing requirements in terms of the various types of correction required. Given this information, MVP which use Artificial Intelligence (AI) Planning techniques to derive unspecified required processing steps and determines appropriate Image processing programs and parameters to achieve the specified Image processing goals. This information is output as an Executable Image processing program which can then be executed to fill the processing request. >

B Mortensenhelen - One of the best experts on this subject based on the ideXlab platform.

H.b. Mortensen - One of the best experts on this subject based on the ideXlab platform.

  • Automating Image processing for scientific data analysis of a large Image database
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996
    Co-Authors: Steve Chien, H.b. Mortensen
    Abstract:

    Describes the Multimission VICAR Planner (MVP): an AI planning system which uses knowledge about Image processing steps and their requirements to construct Executable Image processing scripts to support high-level science requests made to the Jet Propulsion Laboratory (JPL) Multimission Image Processing Subsystem (MIPS). This article describes a general AI planning approach to automation and application of the approach to a specific area of Image processing for planetary science applications involving radiometric correction, color triplet reconstruction, and mosaicing in which the MVP system significantly reduces the amount of effort required by Image processing experts to fill a typical request.

A Chiensteve - One of the best experts on this subject based on the ideXlab platform.

Kiwon Kwon - One of the best experts on this subject based on the ideXlab platform.

  • Demand Paging Techniques for Flash Memory Using Compiler Post-Pass Optimizations
    ACM Transactions in Embedded Computing Systems, 2011
    Co-Authors: Kiwon Kwon, Choonki Jang
    Abstract:

    In this article, we propose an application-specific demand paging mechanism for low-end embedded systems that have flash memory as secondary storage. These systems are not equipped with virtual memory. A small memory space called an execution buffer is used to page the code of an application. An application-specific page manager manages the buffer. The page manager is automatically generated by a compiler post-pass optimizer and combined with the application Image. The post-pass optimizer analyzes the Executable Image and transforms function call/return instructions into calls to the page manager. As a result, each function in the code can be loaded into the memory on demand at runtime. To minimize the overhead incurred by the demand paging technique, code clustering algorithms are also presented. We evaluate our techniques with ten embedded applications, and our approach can reduce the code memory size by on average 39.5p with less than 10p performance degradation and on average 14p more energy consumption. Our demand paging technique provides embedded system designers with a trade-off control mechanism between the cost, performance, and energy efficiency in designing embedded systems. Embedded system designers can choose the code memory size depending on their cost, energy, and performance requirements.

  • EMSOFT - Compiler-assisted demand paging for embedded systems with flash memory
    Proceedings of the fourth ACM international conference on Embedded software - EMSOFT '04, 2004
    Co-Authors: Chanik Park, Junghee Lim, Kiwon Kwon, Jaejin Lee, Sang Lyul Min
    Abstract:

    In this paper, we propose a novel, application specific demand paging mechanism for low-end embedded systems with flash memory as secondary storage. These systems are not equipped with virtual memory. A small memory space called an execution buffer is allocated to page an application. An application-specific page manager manages the buffer. The manager is generated by a compiler post-pass and combined with the application Image. Our compiler post-pass analyzes the ELF Executable Image of an application and transforms function call/return instructions into calls to the page manager. As a result, each function of the code can be loaded into memory on demand at run time. To minimize the overhead of demand paging, code clustering algorithms are also presented. We evaluate our techniques with five embedded applications. We show that our approach can reduce the code memory size by 33% on average with reasonable performance degradation (8-20%) and energy consumption (10% more on average) for low-end embedded systems.