Related Experiment Video
Updated: Feb 7, 2026

In Vitro Model of Human Cutaneous Hypertrophic Scarring using Macromolecular Crowding
Published on: May 1, 2020
Quanti.us: a tool for rapid, flexible, crowd-based annotation of images
Alex J Hughes1,2,3, Joseph D Mornin4, Sujoy K Biswas2,5
1Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA.
Abstract:
We describe Quanti.us , a crowd-based image-annotation platform that provides an accurate alternative to computational algorithms for difficult image-analysis problems. We used Quanti.us for a variety of medium-throughput image-analysis tasks and achieved 10-50× savings in analysis time compared with that required for the same task by a single expert annotator. We show equivalent deep learning performance for Quanti.us-derived and expert-derived annotations, which should allow scalable integration with tailored machine learning algorithms.
Related Concept Videos
Genome Annotation and Assembly
¹H NMR of Conformationally Flexible Molecules: Temporal Resolution
Rapidly Varying Flow
¹H NMR of Conformationally Flexible Molecules: Variable-Temperature NMR
Overview of Microsoft Excel as a Data Analysis Tool
RACE - Rapid Amplification of cDNA Ends

