Variable pathlength cell for internal data validation in computer vision

We present a simple variable pathlength cell that validates color data reliability in computer vision for analytical chemistry, using the linear pathlength–absorbance relationship defined by the Beer–Lambert law in data.

Authors

Institutions

Publication Details

Journal
Digital Discovery
Published
2025-01-01
DOI
https://doi.org/10.1039/d5dd00245a
Primary Topic
CCD and CMOS Imaging Sensors
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Variable pathlength cell for internal data validation in computer vision

Aldrik H. Velders, Vittorio Saggiomo, Xiangyu Liu, Namita Sharma
Digital Discovery
CCD and CMOS Imaging Sensors
article

Variable pathlength cell for internal data validation in computer vision

Aldrik H. Velders, Vittorio Saggiomo, Xiangyu Liu, Namita Sharma
article en

Abstract

We present a simple variable pathlength cell that validates color data reliability in computer vision for analytical chemistry, using the linear pathlength–absorbance relationship defined by the Beer–Lambert law in data.

Digital DiscoveryVol. 4(11)
Wageningen University & Research (NL)
China Scholarship Council
Openalex Percentile: Top 73%
CCD and CMOS Imaging Sensors
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.