Udacity open-sources additional driving data
techcrunch.com
techcrunch.com
It's worth pointing out some other awesome datasets, such as:
• https://devblogs.nvidia.com/parallelforall/deep-learning-sel...
• http://data.selfracingcars.com
Any questions I can answer?
edit: or in the .tar with the dataset
(In such countries, a court might recognize the intent behind a claim of public domain from a country where it is possible, but that requires interpretation of the law of the country the creator is from. And it's likely not an option for locals, since the concept does not exist in local law)
Creative Commons created the CC0 license to work around this: it clearly lays out that a work is intended to be released as public domain, and failing that, all possible rights are granted and the creator doesn't intend to limit them in any way with his remaining ones.
Doesn't that defeat the purpose of licenses? The principle of a license is exactly giving up rights on copyrighted work.
(the comparison is appropriate because that non-revocable subset of rights in Germany's Urheberrecht - and other European countries and probably elsewhere - is based on a notion of human rights)
Update 1 - I see there are lot of details here - https://medium.com/udacity/challenge-2-using-deep-learning-t...
A more useful database would be the one Nexar is accumulating.[1] They collect dashcam imagery of events where the driver did a hard brake or the system detected some other hazardous condition. That database could be used to train a system which recognizes trouble before braking starts.
Both systems need a much wider field of view. Probably at least 160 degrees, so cross traffic shows up before the collision.
[1] http://spectrum.ieee.org/cars-that-think/transportation/sens...
Is this adding a tier to that? A gigabyte a second, per car?
(I know, Google has self-driving cars, but forget about that for a moment)
For contrast, one experiment at CERN produces 40TB/sec of sensor data, before downsampling and filtering: https://en.wikipedia.org/wiki/Compact_Muon_Solenoid#Collecti...
As a rearguard defense: Yes, but, what percent of the time is CERN running an experiment [that generates that data]?
According to a quick Google search, average time spent driving is 101 minutes / day.
Totally makes sense that CERN (and, likely, any large Science! efforts) produces that level of burst data, but wouldn't these cars produce more data over time?
As a different topic, a different friend of mine is of the opinion that AI is dependent on the throughput of data through the system; think about the amount of information your body feeds to your brain, and how much time it was doing that before you were capable of communication.
What time length does the data cover? One hour of driving? Two?
Do you have open map data related to the data set?