11 papers with code • 0 benchmarks • 0 datasets
Accuracy metrics analysis to identify applicability scope and discuss explainability and interpretability of the resulting values
The lack of consensus in different works and AP implementations is a problem faced by the academic and scientific communities.
While the field of electricity price forecasting has benefited from plenty of contributions in the last two decades, it arguably lacks a rigorous approach to evaluating new predictive algorithms.
While the automatic recognition of musical instruments has seen significant progress, the task is still considered hard for music featuring multiple instruments as opposed to single instrument recordings.
However, there exist only few metrics for the accuracy measurement of overlapping and multi-resolution clustering algorithms on large datasets.
This paper focuses on the problem of visual saliency prediction, predicting regions of an image that tend to attract human visual attention, under a constrained computational budget.
Music Recommender Systems (mRS) are designed to give personalised and meaningful recommendations of items (i. e. songs, playlists or artists) to a user base, thereby reflecting and further complementing individual users' specific music preferences.