[calibwam]

Off topic: Always define your abbreviations. To find out what CNN stands for here, you either have to read a comment thread on HN, or go to the paper and read the introduction. The linked page doesn't even mention neural networks. And as some other commenter here has mentioned, CNN has other more well known meanings than Convolutional Neural Networks.

[alias_neo]

It was drilled into us in university (engineering) that you spell out abbreviations and acronyms on first use, no matter how well known you think it is.

Some cases I've seen lately seem to forgo this not out of ignorance but as a form of eletism/knowledge gate keeping.

[everdrive]

> Some cases I've seen lately seem to forgo this not out of ignorance but as a form of elitism/knowledge gate keeping.

It's a natural tendency for ingroups. Nearly any video game forum, or anything else that's full of hobbyists will ultimately contain posts that are absolutely full of acronyms. And they're impenetrable. Bear in mind, I'm not defending this behavior, and certainly not disagreeing with you.

[Avamander]

This is why I like Discourse with it's abbreviation explainer. Musicbrainz's community forums have it and it's incredibly nice.

[yjftsjthsd-h]

I'll defend it. Not the elitism, but using jargon/abbreviations/etc. When you're writing something for a larger audience, you should of course target that audience. But when you're on the "inside" writing for people who already have the background knowledge, it's unnecessary friction to stop and think "what terms would a newbie need defined in this?" It breaks the flow of writing/discourse and is probably mostly not needed, because someone coming in not knowing the terms in play can either go look them up, or just ask in their own post. (Granted, this also depends on that being easy; either a jargon dictionary being available, or the forum members being friendly to newbie questions.) I think it's also understandable to apply a small amount of gatekeeping, insofar as that continual beginner questions in the middle of an advanced discussion are just a distraction. The answer to that should be directing them to a more beginner-friendly subforum, but FWIW I do understand why people sometimes act poorly out of frustration.

[ameister14]

The solution to the "unnecessary friction to stop and think "what terms would a newbie need defined in this?"

If you're writing a paper, define every acronym the first time you use it.

If you're in a forum with a set of acronyms known to all, define them in a sticky or the forum readme.

[alias_neo]

Oh no, I understand your point, no misunderstanding here. It's one of the reasons I keep a technical blog, as an engineer, if I learn the hardest thing I've learned this $timeperiod, I want to share it, as clearly and understandably as I can. I fully support and encourage knowledge sharing, and it hurts just that little bit more when I see it being hoarded.

[yazan94]

Seriously? You want to be able to join a community you might not be familiar with and understand the lingo/jargon off the bat? Of course people will abbreviate things when the word/phrase is sufficiently long, commonly used, and the abbreviation mutually understood (brb, tldr, OOP, etc.). There is no elitism involved, if you don't understand something either Google it or ask. No reason to act snobbish because people cater the the most common denominator in a community rather than the lowest.

[alias_neo]

Not exactly, what I'm arguing against is writing something technical, intended to educate non-experts in the field (the experts don't need your report/paper/thing) and then not providing them with the information they need to background research the things you refer to in abbreviations or acronyms.

And I'm not saying this is _my_ solution, this was literally taught to me in engineering first year.

[ksec]

>no matter how well known you think it is.

May be this is specific to I.T or Computer Science? Where there are thousands of abbreviations and acronyms which itself is often the name people use. SQL, DRAM, CPU, HTTP, SRAM, FPGA, URL, TCP/IP, UDP, NAT, DHCP, GPL, etc.

I mean if you are discussing technicals of Neural network you expect your audience to at least know CPU, GPU, and FPGA. And if you are discussing software development I hope I dont have to spell out GPL.

So I dont think it is a form of eletism/knowledge gate keeping. In the age of internet you can search those "acronyms" meant without the full name, which isn't something could be easily done 15 to 20 years ago.

In other industry such as Mobile Wireless Networking, those acronyms are often clearly spell out because there are comparatively little of it. FDD, TDD, MIMO, NR or LTE are often spelt out in full when they first use.

[franga2000]

> And if you are discussing software development I hope I dont have to spell out GPL.

I'm my university first-year CS class, a third of the students had never heard of GitHub. Now, that's easy to look up, and GPL seems to be a lucky acronym as well, but CNN certainly isn't. Expanding it the first time or adding a footnote costs you nothing, but people not right in your field or still learning tremendously. Someone who got their Master's in CS 10 years ago likely wouldn't have heard of CNNs at all, and neither would most new CS students.

A scientific publication in such a broad field with such a widely-applicable topic and one of the most clashing acronyms right in the title should most certainly at least expand their key terms.

[alias_neo]

I agree with all of that, however, I still stand by; if you're writing a technical document/paper you should spell out all of them, it's just how I was taught.

It doesn't have to be a hard rule, but major topics of a subject should be spelled out, at least, then you're giving people something to work with in their web search.

[logfromblammo]

You spell it out the first time, and if you intend to use it as an acronym later, you put the acronym in parentheses immediately following.

For example: images generated by convolutional neural networks (CNN) are easy to identify.

[tatersolid]

Even something like a major country shouldn’t always be abbreviated:

UK reports rampant student marijuana use before class

That headline has quite a different meaning if “UK” is abbreviating “United Kingdom” versus “University of Kentucky”.

[ImaCake]

The same could be said for my biology education. But it never seems to stop those biologists publishing papers from invocing obscure acroynms and phrases without definition.

[TazeTSchnitzel]

The HTML <abbr> element is perfect for this!

[bilekas]

Genuinely thought this was some reference to something on the topic of 'fake news' Abbreviations are great if you're using the term multiple time. Not as an intro.

[qubex]

I also thought it was a reference to a manner of distinguishing genuine Cable News Network (CNN) screenshots from doctored ones divulged by “fake news” outlets.

[briandear]

I would find it more likely that it was a reference to determine if CNN was being objective and truthful.

https://en.m.wikipedia.org/wiki/CNN_controversies

[usmannk]

This is a paper that was published in CVPR (Conference on Computer Vision and Pattern Recognition). In that context it is unambiguous that CNN means Convolutional Neural Networks.

[pedrocx486]

In that context, yes. But in the context of (eg) a person that just happened to drop here on HN for a quick read, it makes no sense in the headline.

[Cthulhu_]

Where would you draw the line though? Would you want the same for e.g. HTML? HTTP? HN? YC?

I mean personally I'm all in favor of more usage - or even automatic insertion - of the `<abbr>` tag. Can probably be done with a browser addon as well.

[kristopolous]

"CNN generated Image" sounds like "Images generated by the Cable News Network, CNN" as if the corporation has some software/policy for editing and prepping images in a way they can be detected. It's not so absurd, photojournalism can be quite specific in rules.

The ability to classify photos by news outlet based on identifying their photojournalism rules through computer algorithms sounds like a remarkably clever idea.

HTML doesn't have that ambiguity.

[kerakaali]

I wonder if part of an issue is the generation gap? For older readers, I imagine that they're much more familiar with CNN referring to the Cable News Network. Whereas for younger readers heavily involved in tech, me included, we aren't as heavily tied to the former abbreviation, so CNN referring to neural networks comes more readily to mind.

[pedrocx486]

Well, I'm not "old" (which ever the definition is) yet. I'm just on the Front-End side of the dev world. Never fiddled with AI/Neural Networks.

[littlestymaar]

> Where would you draw the line though? Would you want the same for e.g. HTML?

The day someone uses “HTML” to mean “hyper-threaded machine learning” or whatever, yes definitely.

CNN was unambiguously used for the TV channel for decades now, of course some people are confused when one uses it to mean something else without warning.

[kd5bjo]

It’s all about audience and confusion. My feel of the HN readership is that it’s a vey broad base of mostly technical backgrounds; international but US heavy. That puts the ones you list as perfectly reasonable, and CNN referring to the neural networks is usually ok.

I this case, however, there’s a conflict with the news network which could also plausibly be the subject of the headline. They have interenational recognizability, and have been using the acronym almost exclusively for years; it is effectively their name.

[eknkc]

Maybe when it is a widely known abbreviation for something else?

We are not computer algorithms here. A human being can decide "yeah this sounds like cable news network" and use the long form of this CNN.

[m12k]

One relatively easy to draw line is whether the abbreviation has other commonly used meanings. CNN has, while none of HTML, HTTP, HN or YC do.

[jerrre]

That really depends on the reader...

[Piskvorrr]

RMTG OSPG NNZA BZZZRAMT

https://trends.google.com/trends/explore?geo=US&q=%2Fm%2F0x2...

[qubex]

HTML has no alternative interpretation in widespread usage so it is appropriate for use in any context where average general knowledge can be assumed.

HN is suitable here because it can be assumed that Hacker News denizens are acquainted with a rather obvious shorthand for their own community.

YC... likely as above but might be safer explicated and explained.

[alkonaut]

Somewhere between HTML and CNN. The crowd here is familiar enough with HTML but CNN is not only a smaller abbreviation but also an ambiguous one here.

[jiofih]

Welcome to hacker news.

[GEBBL]

Someone who scanned the front page and didn’t delve into these comments might infere that the American news network CNN artificially generate images for their news stories. That’s how I picked this up.

[Piskvorrr]

Where artificially generated images are improbable. Oh wait.

Also, let me quote the linked page:

> malicious use of fake imagery is likely be deployed on a social media platform

Nope, that couldn't possibly relate to any news network. Never never never gonna admit that!

[rplnt]

Not really, I just thought that CNN (the news network) uses generated images in their articles. The topic about recognizing them, or even generating them, would make sense in CVPR.

[notatoad]

If that were their justification, they wouldn't need to define the acronym in the paper. However, in the introduction section of the actual paper they do define CNN. But they use the acronym 9 times before defining it, which is what's kinda weird.

And the website isn't published in the CVPR, it's published on the internet.

[deepnet]

I found CNN a bit confusing, even though I did guess it meant Convolutional Neural Net.

Perhaps my pre-caffeine morning brain is overly pedantic but Generative Nets use deconvolutions to generate images from latent codes, so using CNN rather than GAN (Generative Adversarial Network) is a bit confusing in this context.

CNNs are used by VAEs (Variational AutoEncoders, also generative) use convolutions to produce the latent codes and the discriminator (adversarial) part of GAN training uses convolutions.

I think Generative Networks ( or GNNs ;-) ) would perhaps have been clearer.

[p1esk]

GANs use transposed convolutions to generate images. I haven’t seen anyone use a true deconvolution operation in deep learning. Not even sure it’s possible to invert the result of a convolutional layer, because it’s lossy.

[lp251]

"Transposed convolution" was called "deconvolution" for a short period of time. The authors apparently weren't aware that "deconvolution" has meant "the inverse problem of recovering a convolved signal" since at least the 70s.

[mihaaly]

Either the paper should not be presented elsewhere or should speak out the meaning!

Did they really hoped for that their paper will remain in a specific group of experts? I seriously doubt so.

[taytus]

Yeah, we are not in that context, aren't we?

[pmelendez]

Also, the original authors are not necessarily the ones that posted it in here.

[OJFord]

It seems fair enough in the title to me, but not spelling it out on first use in the abstract is poor IMO.

Edit: Although, I see it does in first use in the introduction, so maybe that's just conforming to whoever's style guide.

[kick]

The character limit is 80. Many abbreviations on the front-page are almost certainly caused by the low character limit making it difficult to express concepts that don't have a singular word for them.

[mr-ron]

The article itself only refers to it as CNN, and doesnt have an actual definition of the abbreviation

[nl]

This github page is intended as an appendix to the paper[1] which does define it:

"However, these methods represent only two instances of a broader set of techniques: image synthesis via convolutional neural networks (CNNs)."

[1] https://arxiv.org/pdf/1912.11035.pdf

[lingodayz]

Glad to read that I was not the only one struggling with this. It reminded me of that [jargon is bad study](https://www.sciencedaily.com/releases/2020/02/200212084357.h...) that came out recently.

[SkyBelow]

I think it depends upon the audience and the work being written. Anything on the level of a news article definitely should spell it out, but a forum post about some game can get away with the common acronyms used by the community. It is part of knowing your audience.

[mbostleman]

Yes, with an abbreviation like CNN it is remarkably presumptuous to not define it in this article. I followed the headline specifically because it was in the title and I assumed it referred to the news network.

[ropiwqefjnpoa]

Seriously, what does CNN mean for most people, even on HN.

Would this be receiving as much attention if they had used "Convolutional Neural Networks" instead of just CNN?

[mikorym]

I thought this was about the news channel.

[dillonmckay]

What does HN abbreviate?

[briandear]

Hacker News

[Grimm1]

I work a decent bit with ML and even with that I'm just waking up and read that as the news Network so apparently pretty easy to confuse

[currymj]

it’s a scientific paper from a computer vision conference, it would be absurd in that context to assume anyone reading it doesn’t know that it stands for convolutional neural network. they didn’t write this with Hacker News in mind.

[danmg]

It's not ambiguous which CNN they meant from the rest of the words in the title.

[IAmEveryone]

What's "HN"?

[amelius]

Also, the convolution part is only a speedup thing. You can do very similar neural network operations without the convolution, except that everything will be much slower and you'd need a lot more memory.

[gjm11]

It's not really "only a speedup thing" because the training process is different: as a CNN learns to (say) recognize dog-noses in the top left portion of the image, it's simultaneously learning to recognize dog-noses everywhere else too. A fully-connected MLP with the same layer structure doesn't have that property.

It's true that once you've trained your CNN you could make a non-convolutional NN that computes exactly the same things but less efficiently, but the point of an NN is not just what it can compute -- there are lots of systems that can, given enough parameters, approximate arbitrary functions well -- but how you train it.

[amelius]

Yes that's why I said "very similar". Without a convolution, you will have to replicate a lot of the network structure, and you'd have to train with shifted versions of your data. But fundamentally the convolution only gives an advantage in speed and memory, not in functionality.