Categories: AI/ML News

New technique can automate data curation for self-supervised pre-training of AI datasets

A team of computer scientists and AI researchers from FAIR at Meta, INRIA, Université Paris Saclay and Google, has developed a possible means for automating data curation for self-supervised pre-training of AI datasets.

SeMAnD: Self-Supervised Anomaly Detection in Multimodal Geospatial Datasets

*= Equal Contributors We propose a Self-supervised Anomaly Detection technique, called SeMAnD, to detect geometric anomalies in Multimodal geospatial datasets. Geospatial data comprises acquired and derived heterogeneous data modalities that we transform to semantically meaningful, image-like tensors to address the challenges of representation, alignment, and fusion of multimodal data. SeMAnD…

November 9, 2023

In "FAANG"

Label-Efficient Sleep Staging Using Transformers Pre-trained with Position Prediction

Sleep staging is a clinically important task for diagnosing various sleep disorders but remains challenging to deploy at scale because it requires clinical expertise, among other reasons. Deep learning models can perform the task but at the expense of large labeled datasets, which are unfeasible to procure at scale. While…

April 30, 2024

In "FAANG"