Featured papers

Read a featured selection of Visual Intelligence publications.

You can find all Visual Intelligence publications here

Reinventing Self-Supervised Learning: The Magic of Memory in AI Training

Updated
July 29, 2024
MaSSL is a novel approach to self-supervised learning that enhances training stability and efficiency.

Researchers at Visual Intelligence develop novel AI algorithm for analyzing microfossils

Updated
June 8, 2024
- This work shows that there is great potential in utilizing AI in this field, says researcher Iver Martinsen.

Interrogating Sea Ice Predictability With Gradients

Updated
February 14, 2024
The paper focuses on interrogating the effect of the IceNet's input feature with a gradient-based analysis.

Merging clustering into deep supervised neural network

Updated
June 4, 2023
Introducing the SuperCM technique to significantly improve classification results across various types of image data.

Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-shot Learning with Hyperspherical Embeddings

Updated
March 6, 2023
We approach the representation learning task by tackling the hubness problem.

On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering

Updated
March 6, 2023
We propose DeepMVC – a unified framework which includes many recent methods as instances.

New Visual Intelligence paper accepted to NeurIPS

Updated
September 15, 2022
ProtoVAE explainability paper by Srishti Gautam and co-authors is published to NeurIPS 2022.

Multi-modal land cover mapping of remote sensing images using pyramid attention and gated fusion networks

Updated
July 1, 2022
We present a novel pyramid attention and gated fusion method (MultiModNet) for multi-modality land cover mapping in remote sensing.

Principle of Relevant Information for Graph Sparsification

Updated
May 20, 2022
How can we remove the redundant or less-informative edges in a graph without changing its main structural properties?