During an offline phase, a small set of training input images (20 images) is selected on which a human operator manually segments skin regions.
They automated a process by evaluating the quality of a view, captured by every single camera, for which a human producer manually selects the best view in [16].
Let us visualize the various approaches in Fig. 1: Scenario A shows typical unsupervised ML: the algorithm is applied on the raw data and learns fully automatic, because it does not require a human to manually label the data.
As described earlier, to create a database entry, a human operator manually positions the trace mobile, initiates the scan, and labels the resulting RSS vector with its class index (i.e., room number).
While the 500 km figure may be too large to disentangle neighbouring cities, the number of tweets surfaced by our method is small enough that a human could manually read through them before any action is taken.
In contrast to fully automated methods presented so far, Nissim et al. propose to use an active learning approach, where a human expert manually labels interesting samples for a machine learning algorithm, with the goal of keeping the detector up-to-date with the newest threats [23].
In other words, our algorithm has been designed having in mind the way a human would manually detect wave activity by looking at a wavelet spectra; namely, by looking for portions of the wavelet spectrum where wavelet power appears to be significantly higher than in the surrounding and the frequency around which the enhancement in wavelet power is centred varies with time in some regular way.
A human would manually review only the citations deemed relevant by the classifier.
After uploading IntAct, MINT and DIP, their PPI data were further processed based on information from UniProtKB to include only interactions between two active primary UniProt identifiers in the human manually reviewed "complete" proteome.
