ReviewPlant methods2021
Computer vision-based wood identification and its expansion and contribution potentials in wood science: A review.
Review in Plant methods, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed, 112 citations in OpenAlex.
- How much cross-sectional area is needed to estimate vessel traits in tropical tree branches?Annals of botany · 2026Article
- An Improved YOLOv8 Detection Algorithm Based on Screen Printing Defect Images.Sensors (Basel, Switzerland) · 2026Article
- Research on Augmentation of Wood Microscopic Image Dataset Based on Generative Adversarial Networks.Journal of imaging · 2025Article
- The pipelines of deep learning-based plant image processing.Quantitative plant biology · 2025Review
- Performance of convolutional neural network (CNN) and performance influencing factors for wood species classification of Lepidobalanus growing in Korea.Scientific reports · 2024Article
- Opening the black box: explainable deep-learning classification of wood microscopic image of endangered tree species.Plant methods · 2024Article
- Probing the complexity of wood with computer vision: from pixels to properties.Journal of the Royal Society, Interface · 2024Article
- From Industry 5.0 to Forestry 5.0: Bridging the gap with Human-Centered Artificial Intelligence.Current forestry reports · 2024Review
- How to discriminate wood of CITES-listed tree species from their look-alikes: using an attention mechanism with the ResNet model on an enhanced macroscopic image dataset.Frontiers in plant science · 2024Article
- SmartWoodID-an image collection of large end-grain surfaces to support wood identification systems.Database : the journal of biological databases and curation · 2023Article
- Quantitative morphological transformation of vascular bundles in the culm of moso bamboo (Phyllostachys pubescens).PloS one · 2023Article
- Wood identification ofFrontiers in plant science · 2023Article
- Intra-annual fluctuation in morphology and microfibril angle of tracheids revealed by novel microscopy-based imaging.PloS one · 2022Article
- Creating High-Resolution Microscopic Cross-Section Images of Hardwood Species Using Generative Adversarial Networks.Frontiers in plant science · 2021Article
- Towards Sustainable North American Wood Product Value Chains, Part I: Computer Vision Identification of Diffuse Porous Hardwoods.Frontiers in plant science · 2021Article
- Mask, Train, Repeat! Artificial Intelligence for Quantitative Wood Anatomy.Frontiers in plant science · 2021Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
Abstract
The remarkable developments in computer vision and machine learning have changed the methodologies of many scientific disciplines. They have also created a new research field in wood science called computer vision-based wood identification, which is making steady progress towards the goal of building automated wood identification systems to meet the needs of the wood industry and market. Nevertheless, computer vision-based wood identification is still only a small area in wood science and is still unfamiliar to many wood anatomists. To familiarize wood scientists with the artificial intelligence-assisted wood anatomy and engineering methods, we have reviewed the published mainstream studies that used or developed machine learning procedures. This review could help researchers understand computer vision and machine learning techniques for wood identification and choose appropriate techniques or strategies for their study objectives in wood science.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.