  Deep learning method develops very fast as a tool for data analysis these
years. Such a technique is quite promising to treat gravitational wave
detection data. There are many works already in the literature which used deep
learning technique to process simulated gravitational wave data. In this paper
we apply deep learning to LIGO O1 data. In order to improve the weak signal
recognition we adjust the convolutional neural network (CNN) a little bit. Our
adjusted convolutional neural network admits comparable accuracy and efficiency
of signal recognition as other deep learning works published in the literature.
Based on our adjusted CNN, we can clearly recognize the eleven confirmed
gravitational wave events included in O1 and O2. And more we find about 2000
gravitational wave triggers in O1 data.
