Concepedia

Image-based Damage Quantification

Image-Based Damage Quantification is a computational method that belongs to the class of damage assessment techniques and is specifically distinguished by its use of digital image analysis to objectively measure and quantify nematode-induced plant tissue damage through spatial, textural, or colorimetric features derived from visual data.

105

Publications

4.9K

Citations

441

Authors

222

Institutions

Publications per year

2017–2026

53

Parents

Publications

105

Digital image correlation studies for microscopic strain distribution and damage in dual phase steels

Jian Kang, Y. Ososkov, J.D. Embury et al. · Scripta Materialia · 2007 · 319 citations

, , +16

Improved Image Analysis for Evaluating Concrete Damage

Tara C. Hutchinson, Zhiqiang Chen · Journal of Computing in Civil Engineering · 2006 · 237 citations

, , +16

Deep learning-based automatic volumetric damage quantification using depth camera

Gustavo H. Beckman, Dimos Polyzois, Young‐Jin Cha · Automation in Construction · 2018 · 208 citations

, , +11

Emerging non-destructive imaging techniques for fruit damage detection: Image processing and analysis

Naveen Kumar Mahanti, R. Pandiselvam, Anjineyulu Kothakota et al. · Trends in Food Science & Technology · 2021 · 183 citations

, , +15

Early detection of mechanical damage in mango using NIR hyperspectral images and machine learning

Nayeli Vélez Rivera, Juan Gómez‐Sanchís, José Jorge Chanona‐Pérez et al. · Biosystems Engineering · 2014 · 165 citations · Full text

, , +16

1–5 of 105

Authors

441

  1. JS
    Junwon Seo

    South Dakota State University, United States

    3 publications · 148 citations

    3

    h-index

  2. ZC
    Zhiqiang Chen

    University of Missouri–Kansas City, United States

    3 publications · 314 citations

    3

    h-index

  3. JP
    James P. Wacker

    Forest Products Laboratory, United States

    3 publications · 148 citations

    3

    h-index

  4. RS
    Rattapon Saengrayap

    Mae Fah Luang University, Thailand

    2 publications · 50 citations

    2

    h-index

  5. KP
    Krzysztof Przybył

    University of Life Sciences in Poznań, Poland

    2 publications · 30 citations

    2

    h-index

1–5 of 441

Institutions

222

  1. Agricultural Research Service

    Washington, United States

    6 h-index

    9 publications

    381 citations

  2. Drexel University

    Philadelphia, United States

    4 h-index

    14 publications

    1.3K citations

  3. Centre National de la Recherche Scientifique

    Paris, France

    4 h-index

    12 publications

    517 citations

  4. South Dakota State University

    Brookings, United States

    3 h-index

    5 publications

    227 citations

  5. Forest Products Laboratory

    Madison, United States

    3 h-index

    3 publications

    148 citations

  6. National Agriculture and Food Research Organization

    Tsukuba, Japan

    3 h-index

    6 publications

    110 citations

  7. North Carolina State University

    Raleigh, United States

    2 h-index

    6 publications

    124 citations

  8. Beltsville Agricultural Research Center

    Beltsville, United States

    2 h-index

    2 publications

    46 citations

1–8 of 222

Venues

  1. Computers and Electronics in Agriculture

    8 publications · 448 citations

    8

    h-index

  2. Sensors

    3 publications · 135 citations

    3

    h-index

  3. Postharvest Biology and Technology

    3 publications · 158 citations

    3

    h-index

  4. Crop Science

    2 publications · 100 citations

    2

    h-index

  5. 2

    h-index

1–5