EfficientNet was first proposed in the original paper of Mingxing Tan & Quoc V Le in 2019, namely EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.
iToBoS is exploring the use of EfficientNet models for pigmented skin lesion classification. This family of models, developed by Google researchers, are deep learning architectures that offer exceptional performance.
Test datasets serve as a benchmark to evaluate the performance of algorithms and models.
I-JEPA, the latest self-supervised model from Meta AI, has been officially released: the paper was published in June 2023 at the last CVPR conference, together with their codes that they made open-source.
Naevi (moles) are benign brown or black spots on your skin that sometimes look similar to melanomas, but are completely harmless.
In two previous blog posts, we explained the coma aberration effect that gravity introduced on the standard liquid lenses from Optotune and how it has been solved in the latest generation of the lenses.
The European Commission has organised a series of 3 invitation-only online workshops for consortium members of EU-funded projects and initiatives on data-driven approaches in Cancer Research and data infrastructures relevant to cancer.
iToBoS representatives joined and participated in this event, aimed at exploring how Artificial Intelligence powered by health data sharing can transform cancer challenges into remarkable opportunities.