If you publish in a journal that has closed access, there is generally no fee to publish.

What field are you in? In the life sciences, there’s normally a fee to publish closed-access and a higher one for open-access. My last paper was open access and costed about 3500, compared to 1500 pay walled.

Jibberish.

This is actually an amazing idea

Wish I could help, but my knowledge is negligible in this regard. However, I believe your question came up before on image.sc. Some people seem to be using NetBeans for debugging?

For example here and maybe here.

Perhaps @MurphysLab@lemmy.ca can help? If not, you could try posting on image.sc?

Always thought it’s a play on machine learning, but I’m most probably wrong.

Mate… I’m not saying you’re wrong, but if I don’t see the paper for myself, I’m inclined to be critical of your summary of it. I don’t disagree that it is plausible conservatives indeed are more wealthy, but you have too many assumptions in your comment for any proper conclusion to be taken.

And the idea about altruism isn’t really mine, it’s a very very old and still existing idea in philosophy. Of course it has proponents and opponents, but it hasn’t really been rejected to a degree sufficient to dismiss it, it just remains like pretty much all philosophical concepts, debated. So claiming it is false is a bit arrogant, especially without a proper argument. It would be like claiming free will exists or doesn’t exist with confidence (and this analogy is ironic because egoism is a significant part of the free will debate).

And btw, before you think I’m defending conservatives, you should know I’m a scientist, so I am critical of anything and everything until I see the evidence, and even then, I am critical of the way the evidence was gathered and how it was interpreted. I’m not trying to be “pedantic,” I’m trying to be accurate, because a minute twist on the truth makes it false.

Potentially controversial comment:

rich people with no morals live longer, because they’re entirely self interested, and being entirely self interested they can afford healthcare, thus living longer than non-conservatives on average.

From a philosophical point of view, everyone with absolutely no exception is “self interested.” I believe the idea you’re talking about is whether bettering the lives of other has been incorporated in your identity at a young age making your self-interest ultimately beneficial for others. It’s a complex topic, but the idea is that you don’t really truly do anything for others, ever, but if someone convinced you that if you don’t do good by others, then you should be ashamed or that if you do, you’re a better person, then you do good for others for your own sake, to view yourself in a better light.

I’m a bit confused about your comment though. Are you arguing that the study found that rich people skew the data because of their longer life? If so, I find that hard to believe given the proportion of “rich people,” and the consequently negligible ability to statistically skew a population if it were actually randomly sampled.

Seems to work

I absolutely agree with you about HR writing the postings and the transient obsession with buzzwords. However, I think there’s some hard truth to AI displacing classical image analysis approaches or limiting it to pre and post processing. There are many serious issues with AI (deep learning specifically) as an approach for sure, such as black box modeling which gets in the way of rational scientific inquiry, the need for very large data sets for proper convergence, and maybe even hallucination in advanced models. But these issues are a) possibly resolved within a few years with approaches like explainable AI and statistical sampling for the data size perhaps, and b) don’t negate the advantages of simpler AI approaches.

For example, I think supervised machine learning is incredibly useful for allowing complex tasks like segmenting weird objects (like glial cells) and there are even some well established deep learning models for segmenting such things too. So it can be very useful to employ such strategies for certain steps in a pipeline, but making the entire pipeline one giant model is very difficult and unreliable.

Digital pathology is becoming a proper field very quickly, I just hope I can find a footing somewhere in it, because I found myself becoming extremely passionate about image analysis and my career future is looking a bit shakey.

It’s becoming increasingly clear that image analysis is really heading for being a domain of artificial intelligence. It’s a bit scary, because as a physiologist with no background in computer science, I find it very difficult to find positions in bio image analysis since most seem to ask for anything from advanced experience in supervised machine learning to full blown deep learning model development and spatial statistics. But it’s a good thing for science, just not for amateurs who would like to build a career in the field like me…

Can’t believe I didn’t know about this. Thanks a lot! This should shave several lines off my macros.

Haha yeah I got lucky :D

Okay, so I solved the issue for anyone curious. The improvement is a 59% faster computation, so days/over a week saved in terms of the big picture.

The new approach: I simply create a Euclidean distance map where each non zero pixel is now value-encoded with it’s distance from my coords. I do that with just two ramps, the Euclidean distance equation, and image arithmetic. And then simply threshold the image after getting min and max. Of course a few things to resolve equidistant pixels and such, but all good.

That last neighbor bit.

Editor: remember, you need to have a statement about negatives or limitations, can’t have only positives.

Writer: uhh you got it, boss, I’m sure I can think of something.