The Deep Learning is a new developing learning technology that can be used to detect illegally parked vehicles with 99% success.
If you live in a city and you intend to buy a car, in addition to road taxes you should also consider the cost of parking. In fact, you should calculate the cost of calls for illegal parking that you will accept at some point.
And that's because as technology develops, automatic road policing measures increase. Last month at congress 2017 International Conference on Deep Learning Technologies a team of researchers from Xidian University in China demonstrated a detection system based on Deep Learning and which can diagnose cars who have parked illegally with 99% accuracy.
The system described in the conference uses what is known as the Single Shot Multibox Detector (SSD). This is a kind neuronal network that simplifies the task of detecting objects with the creation of a set of predefined "start boxes". When scanning begins, the algorithm compares the contents of these boxes to some basic level.
A prediction model is produced from object observations.
The Xidian team's method detects cars and so things in terms of processing the objects are a bit simpler because the cars are pretty much the same. This reduces the computational complexity of the processors, allowing the new system to run in real time.
Detection of illegal parking does not take place for the first time.
A similar experimental one program had been implemented in Maryland a few years ago, achieving accuracy rates of about 95 percent. A critical difference between this system and most other methods is that it was based on magnetic sensors rather than optical identification of objects.
The relative report of the system states that this protects the privacy of citizens. Naturally in Greece 99% is not covered by the law, and for the sake of 1% we will never see it on the busy streets of our cities.
