Closest to our work is the Human Trafficking Deep Network (HTDN)<cite> (Tong et al., 2017)</cite> . HTDN has three main components: a language network that uses pretrained word embeddings and a long shortterm memory network (LSTM) to process text input; a vision network that uses a convolutional network to process image input; and another convolutional network to combine the output of the previous two networks and produce a binary classification. Compared to the language network in HTDN, our model replaces LSTM with a gatedfeedback recurrent neural network, adopts certain regularizations, and uses an ordinal regression layer on top. It significantly improves HTDN's benchmark despite only using text input.