4 papers
Multi-level Attention Model for Weakly Supervised Audio Classification
Changsong Yu, Karim Said Barsim, Qiuqiang Kong +1
In this paper, we propose a multi-level attention model to solve the weakly labelled audio classification problem. The objective of audio classification is to predict the presence…
Neural Network Ensembles to Real-time Identification of Plug-level Appliance Measurements
Karim Said Barsim, Lukas Mauch, Bin Yang
The problem of identifying end-use electrical appliances from their individual consumption profiles, known as the appliance identification problem, is a primary stage in both Non-I…
On the Feasibility of Generic Deep Disaggregation for Single-Load Extraction
Karim Said Barsim, Bin Yang
Recently, and with the growing development of big energy datasets, data-driven learning techniques began to represent a potential solution to the energy disaggregation problem outp…
Selective Sampling and Mixture Models in Generative Adversarial Networks
Karim Said Barsim, Lirong Yang, Bin Yang
In this paper, we propose a multi-generator extension to the adversarial training framework, in which the objective of each generator is to represent a unique component of a target…