Showing 1 - 4 results of 4 for search 'Rowan L Converse' Skip to content
VuFind
    • English
    • Deutsch
    • Español
    • Français
    • Italiano
    • 日本語
    • Nederlands
    • Português
    • Português (Brasil)
    • 中文(简体)
    • 中文(繁體)
    • Türkçe
    • עברית
    • Gaeilge
    • Cymraeg
    • Ελληνικά
    • Català
    • Euskara
    • Русский
    • Čeština
    • Suomi
    • Svenska
    • polski
    • Dansk
    • slovenščina
    • اللغة العربية
    • বাংলা
    • Galego
    • Tiếng Việt
    • Hrvatski
    • हिंदी
    • Հայերէն
    • Українська
    • Sámegiella
    • Монгол
Advanced
  • Author
  • Rowan L Converse
Export Ready — 
Showing 1 - 4 results of 4 for search 'Rowan L Converse', query time: 0.02s Refine Results
  1. 1
    Assessing Drought Vegetation Dynamics in Semiarid Grass- and Shrubland Using MESMA

    Assessing Drought Vegetation Dynamics in Semiarid Grass- and Shrubland Using MESMA by Rowan L. Converse, Christopher D. Lippitt, Caitlin L. Lippitt

    Published 2021-09-01
    Get full text
    Article
  2. 2
    Remote sensing and machine learning to improve aerial wildlife population surveys

    Remote sensing and machine learning to improve aerial wildlife population surveys by Rowan L. Converse, Rowan L. Converse, Christopher D. Lippitt, Christopher D. Lippitt, Mark D. Koneff, Timothy P. White, Benjamin G. Weinstein, Richard Gibbons, David R. Stewart, Abram B. Fleishman, Matthew J. Butler, Steven E. Sesnie, Grant M. Harris

    Published 2024-06-01
    Get full text
    Article
  3. 3
    A framework for assessing reliability of observer annotations of aerial wildlife imagery, with insights for deep learning applications.

    A framework for assessing reliability of observer annotations of aerial wildlife imagery, with insights for deep learning applications. by Rowan L Converse, Christopher D Lippitt, Steven E Sesnie, Grant M Harris, Matthew J Butler, David R Stewart

    Published 2025-01-01
    Get full text
    Article
  4. 4
    A framework for assessing reliability of observer annotations of aerial wildlife imagery, with insights for deep learning applications

    A framework for assessing reliability of observer annotations of aerial wildlife imagery, with insights for deep learning applications by Rowan L. Converse, Christopher D. Lippitt, Steven E. Sesnie, Grant M. Harris, Matthew J. Butler, David R. Stewart

    Published 2025-01-01
    Get full text
    Article

Search Tools:

  • RSS Feed
  • Email Search

Search Options

  • Search History
  • Advanced Search

Find More

  • Browse the Catalog
  • Browse Alphabetically
  • Explore Channels
  • Course Reserves
  • New Items

Need Help?

  • Search Tips
  • Ask a Librarian
  • FAQs