Publications
107
Citations
2,281
Est. group size
—
Recurring co-author estimate
Active years
28
Publishing since 1999
Alex C. Wiedenhoeft works on wood science, focusing on identifying tree species from wood samples using microscopic and macroscopic image analysis, computer vision, and machine learning. This research supports efforts to combat illegal logging and timber fraud, verify sustainable wood products, and build practical identification tools like smartphone apps and field manuals for use in North America, Central America, the Caribbean, and West Africa.
Publication output has fluctuated over the last decade, with peaks around 2019-2020 and 2022, a dip in 2023-2024, and a recent uptick in 2025, averaging about 3.6 papers per year over the last five years.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- A typology for visual cues delimiting growth ring boundaries and a deep learning model to detect them in macroscopic images of softwoods
IAWA Journal - KU Leuven/IAWA Journal · 2026
- A deep learning model to detect growth ring boundaries in macroscopic images of diffuse-porous hardwoods
IAWA Journal - KU Leuven/IAWA Journal · 2026
- Hidden legacies: Investigating buried pre-colonial stream corridors in the Mid-Atlantic Coastal Plain, Maryland, USA
Ecological Engineering · 2025
- WhatWood? Ghana Edition: Enhancing a Wood Identification Field Manual with Smartphone Functionality
Forest Products Journal · 2025
- Fraud and Misrepresentation in the Lump Charcoal Market in the United States: A Closer Look Inside the Bag
Forest Products Journal · 2025
- Delving into the porosity domain continuum in hardwood growth rings: What can we learn from computer vision wood identification models?
BioResources · 2025
- Democratizing essential wood identification information for Central American timber markets with an ergonomically designed, interactive, bilingual smartphone app
Wood and Fiber Science · 2025
- Predicting hardwood porosity domains: Toward cascading computer-vision wood identification models
BioResources · 2024
- Robustness of a macroscopic computer-vision wood identification model to digital perturbations of test images
IAWA Journal - KU Leuven/IAWA Journal · 2024
- On the possible functions of helical thickenings in conductive cells in wood
IAWA Journal - KU Leuven/IAWA Journal · 2023
- Evaluation Of Test Specimen Surface Preparation On Macroscopic Computer Vision Wood Identification
Wood and Fiber Science · 2023
- Towards Sustainable North American Wood Product Value Chains, Part I: Computer Vision Identification of Diffuse Porous Hardwoods
Frontiers in Plant Science · 2022
- Can quantitative wood anatomy data coupled with machine learning analysis discriminate CITES species from their look-alikes?
Wood Science and Technology · 2022
- Caveat emptor: On the Need for Baseline Quality Standards in Computer Vision Wood Identification
Forests · 2022
- Towards sustainable North American wood product value chains, part 2: computer vision identification of ring-porous hardwoods
Canadian Journal of Forest Research · 2022
- IAWA Journal - KU Leuven/IAWA Journal×7
- Wood Science and Technology×4
- Frontiers in Plant Science×3
- Plant Methods×2
- JOM×2
- Chunge Li
Chemistry · Purdue University West Lafayette
- Ankita Mitra
Environmental Science · Purdue University West Lafayette
- Akane Abbasi
Environmental Science · Purdue University West Lafayette
- Ayman Habib
Environmental Science · Purdue University West Lafayette
- Adnan Firoze
Environmental Science · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
Claim or correct this profile