The integration of digital technologies, e.g., smartphone apps, has been shown to represent an impactful advancement in training for melanoma diagnosis.1
Expanding the concept of Scaled Dot-Product Attention, Vaswani et al. [1] proposed the multi-head attention mechanism.
Conformal prediction offers a solution in uncertainty quantification and simultaneously provides a method for instance classification.
Artificial intelligence (AI) is at its peak right now. And we know its applications in healthcare are numerous. But when it comes to health data labeling, precision is necessary.
The iToBoS project was introduced in the second edition of PhoenixD Magazine.
In Machine Learning, a common technique used to train a robust and generalizable model, is cross-validation. It divides the dataset into multiple subsets, where typically one of them is the validation set and the remainder consist the training set.
The AI, Data, and Data-Dependent Business Models workshop took place between 31 January and 2 February 2024 at Fraunhofer Heinrich Hertz Institute in Berlin.
Leibniz University Hannover has published a new peer-reviewed scientific article in the IOPScience Journal of Optics. The work was supported by iToBoS project, under European Union’s Horizon 2020 grant agreement No 955221.
Every year, the international society for optics and photonics (SPIE) recognizes innovative companies with the Prism Award.
In computer vision, deep learning models have proven instrumental in tackling various tasks, from object detection and segmentation to image classification and analysis.