The Experts below are selected from a list of 276 Experts worldwide ranked by ideXlab platform

Jana Kosecka - One of the best experts on this subject based on the ideXlab platform.

  • acquiring semantics Induced Topology in urban environments
    International Conference on Robotics and Automation, 2012
    Co-Authors: Gautam Singh, Jana Kosecka
    Abstract:

    Methods for acquisition and maintenance of an environment model are central to a broad class of mobility and navigation problems. Towards this end, various metric, topological or hybrid models have been proposed. Due to recent advances in sensing and recognition, acquisition of semantic models of the environments have gained increased interest in the community. In this work, we will demonstrate a capability of using weak semantic models of the environment to induce different topological models, capturing the spatial semantics of the environment at different levels. In the first stage of the model acquisition, we propose to compute semantic layout of the street scenes imagery by recognizing and segmenting buildings, roads, sky, cars and trees. Given such semantic layout, we propose an informative feature characterizing the layout and train a classifier to recognize street intersections in challenging urban inner city scenes. We also show how the evidence of different semantic concepts can induce useful topological representation of the environment, which can aid navigation and localization tasks. To demonstrate the approach, we carry out experiments on a challenging dataset of omnidirectional inner city street views and report the performance of both semantic segmentation and intersection classification.

  • ICRA - Acquiring semantics Induced Topology in urban environments
    2012 IEEE International Conference on Robotics and Automation, 2012
    Co-Authors: Gautam Singh, Jana Kosecka
    Abstract:

    Methods for acquisition and maintenance of an environment model are central to a broad class of mobility and navigation problems. Towards this end, various metric, topological or hybrid models have been proposed. Due to recent advances in sensing and recognition, acquisition of semantic models of the environments have gained increased interest in the community. In this work, we will demonstrate a capability of using weak semantic models of the environment to induce different topological models, capturing the spatial semantics of the environment at different levels. In the first stage of the model acquisition, we propose to compute semantic layout of the street scenes imagery by recognizing and segmenting buildings, roads, sky, cars and trees. Given such semantic layout, we propose an informative feature characterizing the layout and train a classifier to recognize street intersections in challenging urban inner city scenes. We also show how the evidence of different semantic concepts can induce useful topological representation of the environment, which can aid navigation and localization tasks. To demonstrate the approach, we carry out experiments on a challenging dataset of omnidirectional inner city street views and report the performance of both semantic segmentation and intersection classification.

Xiuzhen Cheng - One of the best experts on this subject based on the ideXlab platform.

  • Relay sensor placement in wireless sensor networks
    Wireless Networks, 2008
    Co-Authors: Xiuzhen Cheng, Ding-zhu Du, Lusheng Wang, Baogang Xu
    Abstract:

    This paper addresses the following relay sensor placement problem: given the set of duty sensors in the plane and the upper bound of the transmission range, compute the minimum number of relay sensors such that the Induced Topology by all sensors is globally connected. This problem is motivated by practically considering the tradeoff among performance, lifetime, and cost when designing sensor networks. In our study, this problem is modelled by a NP-hard network optimization problem named Steiner Minimum Tree with Minimum number of Steiner Points and bounded edge length (SMT-MSP) . In this paper, we propose two approximate algorithms, and conduct detailed performance analysis. The first algorithm has a performance ratio of 3 and the second has a performance ratio of 2.5.

  • Strong minimum energy Topology in wireless sensor networks: NP-Completeness and heuristics
    IEEE Transactions on Mobile Computing, 2003
    Co-Authors: Xiuzhen Cheng, Maggie Xiaoyan Cheng, Rahul Simha, Bhagirath Narahari, Dan Liu
    Abstract:

    Wireless sensor networks have recently attracted lots of research effort due to the wide range of applications. These networks must operate for months or years. However, the sensors are powered by battery, which may not be able to be recharged after they are deployed. Thus, energy-aware network management is extremely important. In this paper, we study the following problem: Given a set of sensors in the plane, assign transmit power to each sensor such that the Induced Topology containing only bidirectional links is strongly connected. This problem is significant in both theory and application. We prove its NP-completeness and propose two heuristics: power assignment based on minimum spanning tree (denoted by MST) and incremental power. We also show that the MST heuristic has a performance ratio of 2. Simulation study indicates that the performance of these two heuristics does not differ very much, but; on average, the incremental power heuristic is always better than MST.

Gautam Singh - One of the best experts on this subject based on the ideXlab platform.

  • acquiring semantics Induced Topology in urban environments
    International Conference on Robotics and Automation, 2012
    Co-Authors: Gautam Singh, Jana Kosecka
    Abstract:

    Methods for acquisition and maintenance of an environment model are central to a broad class of mobility and navigation problems. Towards this end, various metric, topological or hybrid models have been proposed. Due to recent advances in sensing and recognition, acquisition of semantic models of the environments have gained increased interest in the community. In this work, we will demonstrate a capability of using weak semantic models of the environment to induce different topological models, capturing the spatial semantics of the environment at different levels. In the first stage of the model acquisition, we propose to compute semantic layout of the street scenes imagery by recognizing and segmenting buildings, roads, sky, cars and trees. Given such semantic layout, we propose an informative feature characterizing the layout and train a classifier to recognize street intersections in challenging urban inner city scenes. We also show how the evidence of different semantic concepts can induce useful topological representation of the environment, which can aid navigation and localization tasks. To demonstrate the approach, we carry out experiments on a challenging dataset of omnidirectional inner city street views and report the performance of both semantic segmentation and intersection classification.

  • ICRA - Acquiring semantics Induced Topology in urban environments
    2012 IEEE International Conference on Robotics and Automation, 2012
    Co-Authors: Gautam Singh, Jana Kosecka
    Abstract:

    Methods for acquisition and maintenance of an environment model are central to a broad class of mobility and navigation problems. Towards this end, various metric, topological or hybrid models have been proposed. Due to recent advances in sensing and recognition, acquisition of semantic models of the environments have gained increased interest in the community. In this work, we will demonstrate a capability of using weak semantic models of the environment to induce different topological models, capturing the spatial semantics of the environment at different levels. In the first stage of the model acquisition, we propose to compute semantic layout of the street scenes imagery by recognizing and segmenting buildings, roads, sky, cars and trees. Given such semantic layout, we propose an informative feature characterizing the layout and train a classifier to recognize street intersections in challenging urban inner city scenes. We also show how the evidence of different semantic concepts can induce useful topological representation of the environment, which can aid navigation and localization tasks. To demonstrate the approach, we carry out experiments on a challenging dataset of omnidirectional inner city street views and report the performance of both semantic segmentation and intersection classification.

Dan Liu - One of the best experts on this subject based on the ideXlab platform.

  • Strong minimum energy Topology in wireless sensor networks: NP-Completeness and heuristics
    IEEE Transactions on Mobile Computing, 2003
    Co-Authors: Xiuzhen Cheng, Maggie Xiaoyan Cheng, Rahul Simha, Bhagirath Narahari, Dan Liu
    Abstract:

    Wireless sensor networks have recently attracted lots of research effort due to the wide range of applications. These networks must operate for months or years. However, the sensors are powered by battery, which may not be able to be recharged after they are deployed. Thus, energy-aware network management is extremely important. In this paper, we study the following problem: Given a set of sensors in the plane, assign transmit power to each sensor such that the Induced Topology containing only bidirectional links is strongly connected. This problem is significant in both theory and application. We prove its NP-completeness and propose two heuristics: power assignment based on minimum spanning tree (denoted by MST) and incremental power. We also show that the MST heuristic has a performance ratio of 2. Simulation study indicates that the performance of these two heuristics does not differ very much, but; on average, the incremental power heuristic is always better than MST.

Guido H. Clever - One of the best experts on this subject based on the ideXlab platform.

  • copper Induced Topology switching and thrombin inhibition with telomeric dna g quadruplexes
    Angewandte Chemie, 2017
    Co-Authors: David M. Engelhard, Julia Nowack, Guido H. Clever
    Abstract:

    The topological diversity of DNA G-quadruplexes may play a crucial role in its biological function. Reversible control over a specific folding Topology was achieved by the synthesis of a chiral, glycol-based pyridine ligand and its fourfold incorporation into human telomeric DNA by solid-phase synthesis. Square-planar coordination to a CuII ion led to the formation of a highly stabilizing intramolecular metal-base tetrad, substituting one G-tetrad in the parent unimolecular G-quadruplex. For the Tetrahymena telomeric repeat, CuII -triggered switching from a hybrid-dominated conformer mixture to an antiparallel Topology was observed. CuII -dependent control over a protein-G-quadruplex interaction was shown for the thrombin-tba pair (tba=thrombin-binding aptamer).

  • Copper‐Induced Topology Switching and Thrombin Inhibition with Telomeric DNA G‐Quadruplexes
    Angewandte Chemie (International ed. in English), 2017
    Co-Authors: David M. Engelhard, Julia Nowack, Guido H. Clever
    Abstract:

    The topological diversity of DNA G-quadruplexes may play a crucial role in its biological function. Reversible control over a specific folding Topology was achieved by the synthesis of a chiral, glycol-based pyridine ligand and its fourfold incorporation into human telomeric DNA by solid-phase synthesis. Square-planar coordination to a CuII ion led to the formation of a highly stabilizing intramolecular metal-base tetrad, substituting one G-tetrad in the parent unimolecular G-quadruplex. For the Tetrahymena telomeric repeat, CuII -triggered switching from a hybrid-dominated conformer mixture to an antiparallel Topology was observed. CuII -dependent control over a protein-G-quadruplex interaction was shown for the thrombin-tba pair (tba=thrombin-binding aptamer).