A vehicle for inspecting a rail, the vehicle comprising: rail inspection sensors (36, 38) configured for capturing transducer data describing the rail; a processor configured for: receiving the transducer data; and processing the captured transducer data to determine whether the captured transducer data identifies a suspected rail flaw, the processing comprising: inputting the captured transducer data as a stream of overlapping sequences in a form suitable for a machine learning system that has been trained to identify patterns in the transducer data that indicate rail flaws, the machine learning system comprising a deep learning convolutional neural network to perform image pattern recognition that is combined with a long short-term memory recurrent neural network to identify rail flaws of the rail of indeterminate length; and receiving an output from the machine learning system, the output indicating whether the captured transducer data identifies a suspected rail flaw; and transmitting an alert to an operator of the vehicle based at least in part on the output indicating that the captured transducer data identifies a suspected rail flaw, the alert including a location of the suspected rail flaw and instructing the operator to stop the vehicle and to perform a repair action, wherein the stream of overlapping sequences comprises a sequence of overlapping 2-dimensional images. rail inspection sensors (36, 38) configured for capturing transducer data describing the rail; a processor configured for: receiving the transducer data; and processing the captured transducer data to determine whether the captured transducer data identifies a suspected rail flaw, the processing comprising: inputting the captured transducer data as a stream of overlapping sequences in a form suitable for a machine learning system that has been trained to identify patterns in the transducer data that indicate rail flaws, the machine learning system comprising a deep learning convolutional neural network to perform image pattern recognition that is combined with a long short-term memory recurrent neural network to identify rail flaws of the rail of indeterminate length; and receiving an output from the machine learning system, the output indicating whether the captured transducer data identifies a suspected rail flaw; and transmitting an alert to an operator of the vehicle based at least in part on the output indicating that the captured transducer data identifies a suspected rail flaw, the alert including a location of the suspected rail flaw and instructing the operator to stop the vehicle and to perform a repair action, wherein the stream of overlapping sequences comprises a sequence of overlapping 2-dimensional images. receiving the transducer data; and processing the captured transducer data to determine whether the captured transducer data identifies a suspected rail flaw, the processing comprising: inputting the captured transducer data as a stream of overlapping sequences in a form suitable for a machine learning system that has been trained to identify patterns in the transducer data that indicate rail flaws, the machine learning system comprising a deep learning convolutional neural network to perform image pattern recognition that is combined with a long short-term memory recurrent neural network to identify rail flaws of the rail of indeterminate length; and receiving an output from the machine learning system, the output indicating whether the captured transducer data identifies a suspected rail flaw; and inputting the captured transducer data as a stream of overlapping sequences in a form suitable for a machine learning system that has been trained to identify patterns in the transducer data that indicate rail flaws, the machine learning system comprising a deep learning convolutional neural network to perform image pattern recognition that is combined with a long short-term memory recurrent neural network to identify rail flaws of the rail of indeterminate length; and receiving an output from the machine learning system, the output indicating whether the captured transducer data identifies a suspected rail flaw; and transmitting an alert to an operator of the vehicle based at least in part on the output indicating that the captured transducer data identifies a suspected rail flaw, the alert including a location of the suspected rail flaw and instructing the operator to stop the vehicle and to perform a repair action, wherein the stream of overlapping sequences comprises a sequence of overlapping 2-dimensional images.