Meta-learning is an efficient approach in the field of machine learning, which involves multiple classifiers. In this paper, a meta-learning framework consisting of stacking meta-...
This paper presents the results of an investigation into the use of machine learning methods for the identification of narcotics from Raman spectra. The classification of spectr...
Tom Howley, Michael G. Madden, Marie-Louise O'Conn...
Modern processors require highly accurate branch prediction for good performance. As such, a number of branch predictors have been proposed with varying size and complexity. This ...
In this contribution, the capacity-achieving input covariance matrices for coherent blockfading correlated MIMO Rician channels are determined. In contrast with the Rayleigh and u...
Recent research activity on stereo matching has proved the efficacy of local approaches based on advanced cost aggregation strategies in accurately retrieving 3D information. Howe...
Federico Tombari, Stefano Mattoccia, Luigi di Stef...