Best Practices for Managing Data Annotation Projects

09/24/2020
by   Tina Tseng, et al.
0

Annotation is the labeling of data by human effort. Annotation is critical to modern machine learning, and Bloomberg has developed years of experience of annotation at scale. This report captures a wealth of wisdom for applied annotation projects, collected from more than 30 experienced annotation project managers in Bloomberg's Global Data department.

READ FULL TEXT

page 1

page 5

page 25

research
06/25/2021

Semantic annotation for computational pathology: Multidisciplinary experience and best practice recommendations

Recent advances in whole slide imaging (WSI) technology have led to the ...
research
12/07/2021

Towards a Shared Rubric for Dataset Annotation

When arranging for third-party data annotation, it can be hard to compar...
research
09/16/2014

DISA at ImageCLEF 2014 Revised: Search-based Image Annotation with DeCAF Features

This paper constitutes an extension to the report on DISA-MU team partic...
research
04/26/2021

Towards Good Practices for Efficiently Annotating Large-Scale Image Classification Datasets

Data is the engine of modern computer vision, which necessitates collect...
research
08/24/2023

Whombat: An open-source annotation tool for machine learning development in bioacoustics

1. Automated analysis of bioacoustic recordings using machine learning (...
research
07/29/2020

Between Subjectivity and Imposition: Power Dynamics in Data Annotation for Computer Vision

The interpretation of data is fundamental to machine learning. This pape...
research
07/16/2023

Analyzing Dataset Annotation Quality Management in the Wild

Data quality is crucial for training accurate, unbiased, and trustworthy...

Please sign up or login with your details

Forgot password? Click here to reset