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 [1], 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 experience gained from the use of machine vision technology has allowed Bosch to master the skills to support iToBoS project objectives.
Artificial intelligence has been a buzzword in medicine for some years, but it is only slowly becoming a practical reality in dermatology, with many ethical and practical considerations to iron out first.
Intelligent Total Body Scanner was presented as a use case for artificial intelligent in medicine in TV program.