Architecture of our neural network, which can classify image-based phase-folded light curves in multiple (in this case, two) passbands with additional numerical input (in this case, the periods) measured in each passband. From left to right: Two light curves for the same variable star in two different passbands, g and r, are the image inputs of the neural network. These images are processed by two identical CNNs and are then concatenated together for a classification based on the image (light curve) information alone. The additional numerical inputs are the passband-dependent periods of the given variable star, which also processed in a much simpler fully connected neural network. These two inputs and their results are concatenated in the end to make the final classification result.