Data masking is the process by which sensitive data is replaced, with data that is unintelligible to the receiver, addressing data security and privacy requirements and regulations.
The success of new scientific research, such as the novel holistic approach for melanoma detection in iToBoS, is increasingly dependent on the efficient storage and processing of copious amounts of data originating from research. Moreover, the scientists often require complex, large-scale platforms based on the coordinated operation of multiple components.
The ability to continuously process and retain new information like we do naturally as humans is a feat that is highly sought after when training neural networks.
Tunable lenses are conceptionally like a human eye. An elastic polymer membrane covers a reservoir containing an optical liquid.
The iToBoS project is usually categorized within the field of medical imaging. However, all the technical solutions used or to be developed in the project, from the optics to the artificial intelligence algorithms, are part of the wider field of machine vision.
The task of real-world noise removal is challenging, as the noise model is highly complex. CNNs have lately achieved state-of-the-art denoising performance, but the networks are extremely large and complicated for a better accuracy.