It’s a way to infer the data without having to create some human engineered and fragile detection method.
The problem of dealing with unreliable signal transmission (i.e. a CNN’s error rate at inferring the data based on their imaging) is well explored. A CNN that fails to correctly read some measurable percentage of time is not much different than a wireless data transmission on a noisy channel.
You solve the problem by encoding the signal so that you can check the data as it comes in to discover and correct for errors. A simple example would be writing the data 3 times so that you could compare the inference on each of the 3 places where the data is written. Modern error checking algorithms can do a lot better than this, space-wise.
CNNs can be trained to have a very high accuracy rate on these kinds of image recognition tasks (especially with a limited symbol set) and they can tune their error correction around the CNN’s error rates so the net result would be a clean and error check and corrected output.
Not to mention that CNNs may not be required of future persons with better imaging technology.
Not sure what to think about that a CNN is involved in the reading process.
It’s a way to infer the data without having to create some human engineered and fragile detection method.
The problem of dealing with unreliable signal transmission (i.e. a CNN’s error rate at inferring the data based on their imaging) is well explored. A CNN that fails to correctly read some measurable percentage of time is not much different than a wireless data transmission on a noisy channel.
You solve the problem by encoding the signal so that you can check the data as it comes in to discover and correct for errors. A simple example would be writing the data 3 times so that you could compare the inference on each of the 3 places where the data is written. Modern error checking algorithms can do a lot better than this, space-wise.
CNNs can be trained to have a very high accuracy rate on these kinds of image recognition tasks (especially with a limited symbol set) and they can tune their error correction around the CNN’s error rates so the net result would be a clean and error check and corrected output.
Not to mention that CNNs may not be required of future persons with better imaging technology.
CNN as in “Central News Network” or “Convoluted Neural Network”?