Tentative interim results are also given for a proposed extension based on spectral clustering, for extending the method to unlabelled data.Greene, J R
To this end, we propose an activity recognition model with labelled and unlabelled data in smart environments. With small amount of labelled data, we discover activity patterns from unlabelled data based on proposed similarity measurement algorithm. Our system does not require large amount of data ...
Moreover, to exploit unlabelled source domain data—which tends to be much more plentiful than labelled data—we adopt a semi-supervised approach. We propose Velodrome, a semi-supervised method of out-of-distribution generalization that takes labelled and unlabelled data from different resources as ...
Activity discovering and modelling with labelled and unlabelled data in smart environments作者: Highlights: • We propose an activity recognition model balancing accuracy, overhead, data labelling. • We propose a similarity measurement method to effectively discover activity patterns. • We perform ...
For the radioactivity that is injected, a dose of < 1% unlabelled radionuclide may already have a big impact, this is a relatively high dose that will distribute to the bones mainly. As the free radionuclide binds to the DTPA that is added in excess, the DTPA-complexed (daughter-)nucl...
The maximal effective concentration (EC50) was calculated by subtracting non-specific-bound activity (assessed by adding an excess of unlabelled sdAb) from total bound activity and plotted in function of 111In-sdAb concentrations. Data are expressed as mean ± SD. b Ex vivo ...
The binding of [125I]annexin V to PS could be blocked in vitro and in vivo by excess of unlabelled annexin V. In either situation, the levels of radiotracer binding in the blocking studies were less than that of control cells. This could be due to the presence of apoptotic cells in ...
Labelled and unlabelled dataSmart environmentsIn the past decades, activity recognition had aroused great interest for the community of context-awareness computing and human behaviours monitoring. However, most of the previous works focus on supervised methods in which the data labelling is known to be...
Combining labelled and unlabelled data in the design of pattern classification systems - Gabrys, Petrakieva () Citation Context ...sed Learning The usual way of building a text classifier consists of two steps: training to get a model and applying that model on unlabeled examples. However, ...
and Malmqvist, K.: Using labelled and unlabelled data to train a multilayer perceptron for colour classi¢cation in graphic arts, In: L. Imam, Y. Kodratoff, A. El-Dessouki and M. Ali (eds), Lecture Notes in Arti¢cial Intelligence 1611, Multiple Approaches to Intelligent Systems, ...