Frontiers

Automated predictive framework using AI and deep learning approaches for early detection and classification of liver cancer

Liver cancer, including hepatocellular carcinoma (HCC), is a leading cause of cancer-related deaths globally, emphasizing the need for accurate and early detection methods. LiverCompactNet classifies ...
C&EN

Surrogate-Assisted Optimization of Highly Constrained Oil Recovery Processes Using Classification-Based Constraint Modeling

Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, Connecticut 06269, United States Center for Clean Energy Engineering, University of Connecticut, Storrs, ...
Frontiers

3D Inundation Mapping: A Comparison Between Deep Learning Image Classification and Geomorphic Flood Index Approaches

Inundation mapping is a critical task for damage assessment, emergency management, and prioritizing relief efforts during a flooding event. Remote sensing has been an effective tool for interpreting ...
acm.org

Deep Learning for AI

Yoshua Bengio, Yann LeCun, and Geoffrey Hinton are recipients of the 2018 ACM A.M. Turing Award for breakthroughs that have made deep neural networks a critical component of computing. Research on ...
GitHub

Model Zoo

Check out the model zoo documentation for details. 16-layer: 7.5% top-5 error on ILSVRC-2012-val, 7.4% top-5 error on ILSVRC-2012-test 19-layer: 7.5% top-5 error on ...
PNAS

Improving the taxonomy of fossil pollen using convolutional neural networks and superresolution microscopy

We demonstrate that combining optical superresolution imaging with deep learning classification methods increases the speed and accuracy of assessing the biological affinities of fossil pollen taxa.
PNAS

Supervised learning through physical changes in a mechanical system

Supervised learning algorithms can learn subtle features that distinguish one class of input examples from another. We explore a supervised training framework in which mechanical metamaterials ...