Schematic illustration of our network. To better study the features extracted by each channel, we feed the distribution maps from the three channels (total, stellar, and X-ray) into the convolutional KAN kernel and fully connected layers, which share the same configuration, and then sum the results y_i to produce the network’s final output Y. The network’s loss function is set to cross-entropy, with its output being a three-class vector corresponding to the probabilities of each class.