Ah, I had a lack of context.
I thought it might be something like that. It is suggesting O. regalis if I “include suggestions not seen nearby.”
This isn’t a big problem for me, and I don’t really need to pursue it. I’ll just input O. spectabilis manually for the time being. Thanks for looking into it.
Is anyone else noting the suggestions of Anseriformes being really bad now? They were reliable before but right now the CV is having trouble recognizing Mallard and Canada Goose.
Please include specific examples, it’s much easier to investigate a problem if we can try to replicate it on our end.
Mallards seem to be usually recognised at Mallard x American Black Duck hybrids, and Canada Geese as Canada Goose x Greylag Goose hybrids.
Yeah, I’m concerned about vision accuracy on avian hybrids & related species. It’s turning out to be a hard problem for the vision system. We don’t train on subspecies, and it may be that we shouldn’t train on any infraspecific taxa. I’m planning to do experiments next month to decide whether we should exclude avian hybrids in future models, or otherwise treat them differently.
The background is that previous versions of the model had far fewer avian hybrid photos to train on. We had a large growth in the number of avian hybrid identifications in the past year and for the first time, our (capped) training data had as many Mallard x American Black Duck photos as Mallard photos and American Black Duck photos. We didn’t exclude them from the training dataset because it wasn’t a known problem, but obviously I’m re-evaluating that now.
Is there any way certain taxa could be trained above the genus level? Many (most?) ciliates (to say nothing of other microbes) are not possible to identify to species with home equipment. Even genus can be quite challenging at times, sometimes impossible without complex staining techniques using chemicals not available to the amateur.
I don’t think that’s possible, since taxa above genus level have many genera under them, which might have completely different habitus. The AI still will suggest families and the like if it finds multiple genera that look similar to the observation.
Genus level is exactly the level I would like to see (this is the typical goal of microbial ID). But since I see no computer vision note on the genus pages, I assume they are not being trained at that level.
“We’ve also released a new feature for taxon pages on the website which allows you to see which taxa are included in the model. This badge only appears on species pages, not pages of genera, families, etc.”
That doesn’t address my question. So to put it clearly: can it be trained at the genus level? If so, how do we know?
yes it can. To quote Alex who runs it, “If enough photos are present at the genus level, but not enough photos for any of the descendent species, then the genus will be placed in the training set”
I posted the quote in my previous reply to explain why the tag symbol doesn’t show up on the genus pages
Fair enough, thanks!
As an aside: from my understanding, “research grade” observations are required for the training, which are very rare for microbial observations. This is for two reasons. 1) very few people are able to identify microbes with any degree of rigor and 2) as I already mentioned, few legitimate IDs are at the species level. I think I read that it’s possible to mark an observation in such a way as to remove the species level requirement from research grade, but this is such an unusual operation that we cannot expect it from most users. So, I suspect the machine suggestions for microbial life will unfortunately continue to be essentially useless. Such is life! Fortunately, it is not a big concern for me, only a “nice to have someday.”
Yes, you can check a box in the DQA that the community ID cannot be improved, and the observation will become research grade at the level of the community ID.
provided the ID is at below family
Yes, I think they were referring to genera anyway, though.
Hopefully once we figure out how to display it in a way that increases clarity without adding confusion, we’ll add a label to indicate when genus or family is in the model because none of its children are. We just haven’t quite worked that out yet.
In the meantime, if you have a question about a specific taxon or group of taxa, I can look it up for you.
Is there any way the CV could be trained on just feathers?
Probably, but it would probably need to learn how to sort the feathers in the categories, like tail, wing, contour, down, etc., to make it easier to identify.
I think the CV doesn’t take life stages of animals into account, so maybe it doesn’t necessarily need to know that? It would still be interesting to try it even if it couldn’t tell what type of feather it is.