Temporal and Spectral Feature Learning With Two-Stream Convolutional Neural Networks for Appliance Recognition in NILM

Non-intrusive load monitoring (NILM) can monitor the operating state and energy consumption of appliances without deploying sub-meters and is promising to be widely used in residential communities. With the rapid increase of electric loads in amount and type, constructing representative load signatures and designing effective classification models are becoming increasingly crucial for NILM. In thi...