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.
MatSeFi@lemmy.liebeleu.de 1 week ago
Not sure what to think about that a CNN is involved in the reading process.
FauxLiving@lemmy.world 1 week ago
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.
pastermil@sh.itjust.works 1 week ago
CNN as in “Central News Network” or “Convoluted Neural Network”?