A. Porto

BioEncoder: a metric learning toolkit for comparative organismal biology

BioEncoder is a metric learning toolkit designed to improve image classification in biodiversity datasets by focusing on data point relationships rather than class separability.

Automated Landmarking via Multiple Templates

This paper introduces MALPACA, an automated landmarking method that outperforms its single-template counterpart by using multiple templates, and presents a K-means-based approach for template selection.

SlicerMorph: An open and extensible platform to retrieve, visualize and analyze 3D morphology

SlicerMorph provides an open platform for retrieving, visualizing, and analyzing 3D morphology data to address challenges in quantitative organismal biology research.

ALPACA: a fast and accurate approach for automated landmarking of three-dimensional biological structures

ALPACA automates 3D landmark placement for morphometric analysis, achieving accuracy comparable to manual methods while being efficient and generalizable across biological structures.

ML-morph: A fast, accurate and general approach for automated detection and landmarking of biological structures in images

The paper introduces ML-morph, a machine-learning pipeline for automated landmarking in biological images, achieving high accuracy and speed compared to manual methods.