At the same time, Net Zero is a global goal and the fashion industry is undergoing a significant change so that textile materials can be reused, repaired and recycled in a sustainable manner.
Limited availability of datasets from unconstrained settings further limits the use of the state-of-the-art segmentation networks, loss functions and learning strategies which have been built and validated for RGB images.
Continuous assessment of task difficulty and mental workload is essential in improving the usability and accessibility of interactive systems.
Advances in tactile-audio feedback technology have created new possibilities for deaf people to feel music.
Thermal imaging-based physiological and affective computing is an emerging research area enabling technologies to monitor our bodily functions and understand psychological and affective needs in a contactless manner.
Background: A smartphone is a promising tool for daily cardiovascular measurement and mental stress monitoring.
We evaluated the performance of the system by training it to recognise 32 material types in both indoor and outdoor environments.
Finally, a data augmentation technique, inspired from solutions for over-fitting problems in deep learning, is applied to allow the CNN to learn with a small-scale dataset from short-term measurements (e. g., up to a few hours).
In this paper, we propose a novel and robust approach for respiration tracking which compensates for the negative effects of variations in the ambient temperature and motion artifacts and can accurately extract breathing rates in highly dynamic thermal scenes.