Many studies have been performed around CCTV operator detection rates in several contexts and with varying results, however it is generally accepted that increasing the number of screens which an operator needs to monitor will decrease the event detection rate and hamper system performance. Ultimately, if an event of interest is not detected by the observers, no response can be formulated. It is therefore quite clear that the observer to camera ratio is important in determining system performance.
(What are Neural networks?)
Much like a newborn child, a neural network will not recognize something it has never seen before, let alone put a name to it. However, if you teach the child that all yellow round objects are in fact tennis balls, then from that point forward the child will have an easier time recognizing tennis balls as it now knows what to look for. The more tennis balls the child sees throughout its life, the less likely it is that the child will misidentify a tennis ball. We can now see how the performance of a neural network is dependent on the extent of its training or “life experience” which is in turn dependent on the volumes of training data available.