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You are confusing two different tasks, identifying a person out of a small comparison group is relatively easy - just deconstruct the face & compare certain fac
by marcus 19y ago
You are confusing two different tasks, identifying a person out of a small comparison group is relatively easy - just deconstruct the face & compare certain facial features. There was a ton of research on the subject and even some working commercial products (my schools AI lab uses one we built as a lock).
Identifying gender is significantly harder.
You want something a lot harder, have them click on the picture of the more attractive person, use data from a hotornot type site (just make sure the data isn't public). Good luck solving that with Support Vector Machines. If you want to generate more data just use build RE-CAPTCHA type system.
- apgwoz 19y agoI don't see why it'd be harder with good features, and after looking at the article again, 35% accuracy was considered a success. Obviously, I'm not as qualified as you in this sense, but it seems logical based on results I've seen (again, admittedly not the same quality as you've probably seen).
- hhm 19y agoI checked on the "obviously, I'm not as qualified as you in this sense" by looking at the user info, and I remembered that "Ideas to monetize new artifical intelligence" thread... so Marcus, sorry if it's offtopic, but how did you solve that problem? Are you doing captchas maybe? :)
- marcus 19y agoDoing CAD - Computer Assisted Diagnosis - working on improving early cancer detection in Mammography.
- deleted 19y ago[deleted]
- marcus 19y agoIn a way I understand trying to apply the algorithm manually for each client is wasteful, negotiation with each client is tiring especially when its with a 7B company. I'm thinking about using the idea I got of building a web-service around it, and letting people find their own uses for it. Considering applying to YC with the idea.
- hhm 19y agoThanks a lot for your reply and details! I was very interested on it.