asploder
Joined 15 years ago
Joined 15 years ago
In my view, that’s one of the better reasons to have ALPRs at all, but you do need strict controls to prevent misuse.
https://www.cira.ca/en/canadian-shield/configure/summary-cir...
More details on the Senakw development are available from the Squamish Nation's website: https://senakw.com/
Alon has continued their work on this subject with a team of other scholars as the "Transit Costs Project": https://transitcosts.com/about/
- “Coaxial” refers to the design of the physical cable (Wikipedia has a better explanation than I can offer)
- CATV refers to “Community Antenna Television”, the first cable systems in the USA, which fed the signal from a shared “community antenna” to homes in areas with poor broadcast reception.
- “Cable” is the generic term for pay-TV and ISP services over coaxial cable
> As a hybrid approach, you could produce a large number of inferred sentiments for words, and have a human annotator patiently look through them, making a list of exceptions whose sentiment should be set to 0. The downside of this is that it’s extra work; the upside is that you take the time to actually see what your data is doing. And that’s something that I think should happen more often in machine learning anyway.
Couldn't agree more. Annotating ML data for quality control seems essential both for making it work, and building human trust.