HIGHLIGHTS
- who: Roberto Meattini and colleagues from the (UNIVERSITY) have published the article: sEMG-Based Minimally Supervised Regression Using Soft-DTW Neural Networks for Robot Hand Grasping Control, in the Journal: (JOURNAL)
- what: The authors propose a novel sEMG-based minimally supervised regression approach capable of performing nonlinear fitting without the necessity for point-by-point training data labelling. To overcome the limitations of state-of-the-art approaches - i.e. point-to-point labelling of the training dataset for supervised learning and unavailability of data fitting capabilities for unsupervised learning techniques - the authors propose an . . .
If you want to have access to all the content you need to log in!
Thanks :)
If you don't have an account, you can create one here.