Technical writing.
Lessons from architecture, integration or UI pattern decisions. Drawn from professional and personal projects.
Multi-datasource Spring Boot: 3 databases, 1 transaction
How we split back-office editing, mobile API reads and analytics into three distinct PostgreSQL databases while keeping atomic transactions across them. Lessons from an accessible indoor navigation back-end.
Visual SLAM ↔ Python: a clean bridge via subprocess
Integrating a C++ Visual SLAM engine into a FastAPI back-end without exotic bindings, then aligning the result on a floor plan using two GPS constraints. Lessons from an indoor mapping back-office.
AI matcher: blending a deterministic score with an LLM verdict
How ApplyDesk scores 100 offers in a fraction of a second in the browser, and keeps the LLM budget reasonable for a reasoned verdict only on those that deserve it.
Computer vision · 2018-2020
Four papers from my research master's at the University of La Rochelle (MIA Laboratory). Detailed summaries here — PDFs are not hosted (IEEE copyright).
Colorizing genuine archival photos: palette + scribbles
CNN colorization networks are trained on colour photos converted to grayscale — ill-suited to genuine archival B&W (silver halide). I improve the output with two hints: an automated global palette + manual scribbles where it matters (flags, monuments).
Colorizing a B&W movie with a salient-colour palette
A palette of 'salient' scene colours (distinct from the 'memorable' ones the network already infers well) is injected into the CNN as an additional input. One palette covers hundreds of frames — well-suited to movie colorization without per-frame scribbling.
Detecting handwriting anomalies via a convolutional autoencoder
A convolutional autoencoder that detects — without annotation — that a portion of text was written by another hand. Tile splitting + partial Radon transform. Discrimination emerges during training via batch-to-batch shuffling.
Visible + NIR information for CNN face recognition
An original VNIR dataset (52 identities, 3 poses) captured by removing the ICF of a consumer camera. Two CNNs compared. Finding: 3-channel full-spectrum beats 4-channel RGB+I, and the blue channel benefits the most from NIR.