Henry Marichal
Senior ML Engineer @ Pento

Hi, I'm Henry Marichal

Computer Vision Researcher | PhD in Image Processing

Senior Machine Learning Engineer at Pento, specializing in deep learning, computer vision, and image segmentation. PhD researcher in automatic tree ring detection with published work and open-source contributions.

5+ Years Experience
Multiple Publications
3 Open Source Tools
Download CV View Projects Publications

About Me

I'm a Senior Machine Learning Engineer at Pento and PhD in Computer Vision with over 5 years of experience developing deep learning solutions for image segmentation and analysis.

I completed my PhD thesis on automatic tree ring detection and analysis, where I developed novel deep learning architectures and open-source tools that are now used by the dendrochronology research community worldwide.

My research focuses on creating efficient, explainable, and impactful AI systems for challenging domains including dendrochronology, medical imaging, and scientific image analysis.

Published peer-reviewed papers

Tools used internationally

Reduced analysis from hours to minutes

Research Interests

Computer Vision

  • Image Segmentation
  • Object Detection
  • Boundary Tracing

Deep Learning

  • U-Net Architectures
  • CNNs & Domain Adaptation
  • Model Optimization

Applied AI

  • Dendrochronology
  • Medical Imaging
  • Scientific Image Analysis

Featured Projects

TRAS logo

TRAS – Tree Ring Analyzer Suite

Professional dendrochronology software with state-of-the-art CV & DL methods

A complete GUI application built with PyQt5 for automatic tree ring detection and measurement. Integrates multiple detection methods (APD, CS-TRD, DeepCS-TRD) with preprocessing, scale calibration, and professional data export capabilities.

Automatic pith & ring detection with deep learning
Scale calibration and physical measurements
CSV & .POS format exports
Python PyQt5 PyTorch OpenCV
🌲

DeepCS-TRD – Deep Learning for Tree Ring Detection

State-of-the-art U-Net-based tree-ring segmentation

A cutting-edge deep learning method achieving superior performance compared to traditional approaches. Includes annotated dataset, benchmarking scripts, and pre-trained models.

Reduces analysis time from hours to minutes
High accuracy on challenging samples
Includes fully annotated dataset
PyTorch U-Net Computer Vision

Selected Publications

For a complete list, visit my Google Scholar profile

Recent Journal & Conference Papers

  1. Marichal, H., Blanco, J., Passarella, D., Randall, G. (2025). UruDendro4: A Benchmark Dataset for Automatic Tree-Ring Detection in Cross-Section Images of Pinus taeda L. IEEE 15th International Conference on Pattern Recognition Systems (ICPRS-25). Accepted.

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  2. Marichal, H., Casaravilla, V., Power, C., Mello, K., Profumo, L., Mazarino, J., Lucas, C., Passarella, D., Randall, G. (2025). DeepCS-TRD, a Deep Learning-based Cross-Section Tree Ring Detector. International Conference on Image Analysis and Processing (ICIAP). Accepted.

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  3. Marichal, H., Passarella, D., Lucas, C., Profumo, L., Casaravilla, V., Rocha Galli, M. N., Ambite, S., Randall, G. (2025). UruDendro, a public dataset of 64 cross-section images and manual annual ring delineations of Pinus taeda L. Annals of Forest Science.

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  4. Marichal, H., Passarella, D., Randall, G. (2025). CS-TRD: a Cross-Section Tree Ring Detection Method. Image Processing On Line (IPOL). Accepted.

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  5. Marichal, H., Passarella, D., Randall, G. (2024). Automatic Wood Pith Detector: Local Orientation Estimation and Robust Accumulation. International Conference on Pattern Recognition (ICPR).

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Under Review & Submitted

  1. Marichal, H., Passarella, D., Randall, G. (2024). TRAS: An Interactive Software for Tracing Tree Ring Cross Sections. Under Review.

  2. Marichal, H., Power, C., Treier, U. A., Resente, G., Normand, S., Randall, G. (2024). Assessing automatic ring detection on microscopy images of Salix glauca. Under Review.

Thesis

  1. Marichal, H. (2025). Application of Image Processing and Artificial Intelligence Techniques for the Automatic Dendrometry of Native and Commercial Wood Species. Doctoral Thesis in Electrical Engineering, Universidad de la República. (Advisors: Gregory Randall and Diego Passarella).

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