Aug. 10, 2023, 4:48 a.m. | Abhishek Kushwaha, Sarthak Gupta, Anish Bhanushali, Tathagato Rai Dastidar

cs.CV updates on arXiv.org arxiv.org

While the use of artificial intelligence (AI) for medical image analysis is
gaining wide acceptance, the expertise, time and cost required to generate
annotated data in the medical field are significantly high, due to limited
availability of both data and expert annotation. Strongly supervised object
localization models require data that is exhaustively annotated, meaning all
objects of interest in an image are identified. This is difficult to achieve
and verify for medical images. We present a method for the transformation …

analysis annotated data annotation artificial artificial intelligence arxiv availability classification cost data data creation expert expertise image images intelligence localization medical training training data

Data Engineer

@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US

Research Engineer

@ Allora Labs | Remote

Ecosystem Manager

@ Allora Labs | Remote

Founding AI Engineer, Agents

@ Occam AI | New York