RESEARCH NOTEBOOK
Practical field notes at the intersection of artificial intelligence, plant phenotyping, imaging, and scientific software.
LATEST NOTES
Concise project records and technical guides, revised to separate verified results from experimental workflows.
A practical guide to using Root Quantify for polygon ROI selection, background correction, binary-mask cleanup, and organized export before downstream root analysis.
A maintainable workflow for choosing a local model, testing it with Ollama, planning parameter-efficient fine-tuning, evaluating results, and exposing a service safely.
A validation-first research framework connecting multi-view reconstruction, plant geometry, radiative transfer, leaf physiology, and canopy-scale uncertainty.
A validation-first workflow for processing DJI P4 Multispectral imagery in WebODM, checking band metadata in QGIS, and extracting plot-level vegetation features.
A concise, reproducibility-focused route from tensors and training loops to transfer learning, evaluation, safe checkpoints, and deployment boundaries.
An experimental, validation-first protocol for acquiring and reconstructing multi-view images of potted cotton plants in a controlled environment.
A practical workflow for structuring Python research projects, recording environments, collaborating through Git, and preserving data provenance.
A safe, modern introduction to repositories, commits, branches, remotes, pull requests, authentication, and undoing mistakes.
A compact, safety-aware reference for everyday macOS, Finder, text-editing, browser, screenshot, and recovery shortcuts.