Showing 161 - 180 results of 2,538 for search '("trapping" OR ((("tapping" OR "stepping") OR ("tapping" OR "stepping")) OR "mapping"))', query time: 0.20s Refine Results
  1. 161

    A web system for map-matching trajectories on road networks by Tan, Fiora Bei Lun

    Published 2022
    “…This process is known as map-matching. Map-matching the GPS data points allows them to provide more value and insights for further analysis. …”
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    Final Year Project (FYP)
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    Building 'Tilesy' : a lean tile map editor in unity by Chen, Chin Jieh

    Published 2017
    “…This report details the research, design, and implementation of Tilesy, a visual tile map editor that facilitates the production of simple but usable tile maps that can be imported and translated into functional game maps by an already existing game editor, ‘Game Editor’. …”
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    Final Year Project (FYP)
  6. 166

    Cross-speaker viseme mapping using hidden Markov models by Dong, Liang, Foo, Say Wei, Yong, Lian

    Published 2009
    “…In this paper, a method of mapping visual speech between different speakers is proposed. …”
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    Conference Paper
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    Genotype-phenotype maps for gene networks: from evolution to computation by Camargo, FQ

    Published 2017
    “…<p>One of the most fundamental and least understood elements of evolution is the mapping between genotype and phenotype. Recent work on genotype-phenotype (GP) maps suggests that these maps show properties which may have important evolutionary implications. …”
    Thesis
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  10. 170

    Combining detection dogs and camera traps improves minimally-invasive population monitoring for the cheetah, an elusive and rare large carnivore by Verschueren, S, Hofmann, T, Schmidt-Küntzel, A, Kakove, M, Munyandi, B, Bauer, H, Balkenhol, N, Leirs, H, Neumann, S, Cristescu, B, Marker, L

    Published 2025
    “…The detection probability (p) of cheetahs with one camera trap station per sampling unit placed at roads was low (p = 0.167), but increased for camera traps placed at marking sites that were identified through the detection dog survey (p = 0.244), and in particular when multiple camera trap stations were placed per sampling unit and detections were pooled across stations (p = 0.348 - 0.750). …”
    Journal article
  11. 171

    Hollow-core photonic crystal fiber based multifunctional optical system for trapping, position sensing, and detection of fluorescent particles by Shinoj, Vengalathunadakal Kuttinarayanan, Murukeshan, Vadakke Matham

    Published 2013
    “…This multifunctional optical system for trapping, position sensing, and fluorescent detection is designed such that a near-IR laser light is used to create an optical trap across a liquid-filled HC-PCF, and a 473 nm laser is employed as a source for fluorescence excitation. …”
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    Journal Article
  12. 172

    First cycle voltage hysteresis in Li-rich 3d cathodes associated with molecular O2 trapped in the bulk by House, RA, Rees, G, Perez-Osorio, M, Marie, J-J, Boivin, E, Robertson, A, Nag, A, Garcia-Fernandez, M, Zhou, K-J, Bruce, P

    Published 2020
    “…The implication is that O2, trapped in the bulk and lost from the surface, can explain O-redox.…”
    Journal article
  13. 173

    Enabling conditions for conservation on indigenous and community lands: a systematic map by Brittain, S, Alatorre, A, Bullough, L-A, Newing, H

    Published 2025
    “…</p> <br> <p>Priorities for future systematic reviews include in-depth examinations of the linkages identified in this map, and the quality of evidence that exists. Understanding how Indigenous Peoples and local communities can best be supported is a critical step in promoting rights-based approaches, as set out in the post-2020 Global Biodiversity Framework.…”
    Journal article
  14. 174

    PlaneSDF-Based Change Detection for Long-Term Dense Mapping by Fu, Jiahui, Lin, Chengyuan, Taguchi, Yuichi, Cohen, Andrea, Zhang, Yifu, Mylabathula, Stephen, Leonard, John J.

    Published 2024
    “…Given point clouds of the source and target scenes, we propose a three-step PlaneSDF-based change detection approach: (1) PlaneSDF volumes are instantiated within each scene and registered across scenes using plane poses; 2D height maps and object maps are extracted per volume via height projection and connected component analysis. (2) Height maps are compared and intersected with the object map to produce a 2D change location mask for changed object candidates in the source scene. (3) 3D geometric validation is performed using SDF-derived features per object candidate for change mask refinement. …”
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    Article
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