To date, machine learning for human action recognition in video has been widely implemented in sports activities.
We conduct the first large-scale empirical study of seven representative GUI element detection methods on over 50k GUI images to understand the capabilities, limitations and effective designs of these methods.
no code implementations • 11 Jun 2020 • Kiran Raja, Matteo Ferrara, Annalisa Franco, Luuk Spreeuwers, Illias Batskos, Florens de Wit Marta Gomez-Barrero, Ulrich Scherhag, Daniel Fischer, Sushma Venkatesh, Jag Mohan Singh, Guoqiang Li, Loïc Bergeron, Sergey Isadskiy, Raghavendra Ramachandra, Christian Rathgeb, Dinusha Frings, Uwe Seidel, Fons Knopjes, Raymond Veldhuis, Davide Maltoni, Christoph Busch
Further, we present a new online evaluation platform to test algorithms on sequestered data.
Fingerprint recognition systems are widely deployed in various real-life applications as they have achieved high accuracy.
However, the prerequisite of using screen readers is that developers have to add natural-language labels to the image-based components when they are developing the app.
In this paper, we propose a general predictor, named multi-view machines (MVMs), that can effectively include all the possible interactions between features from multiple views.