http://Natuurtijdschriften.nl Dialoog met de natuurFrans Vera
https://www.vorsten.nl/vorstenhuizen/nederland/prinses-irene-in-dialoog-met-de-natuur/ https://app.nlziet.nl/vod/vxgR5K_EUW_8BrZqfczKg HILVERSUM – De VARA en de Boeddhistische Omroep Stichting (BOS) zenden zaterdagavond de documentaire Dialoog met de natuur uit, waarvoor ecoloog en filosoof Matthijs Schouten in de Oostvaardersplassen onder anderen in gesprek ging met prinses Irene.
https://www.youtube.com/watch?v=RdOZmR-geek De verdiepende documentaire volgt op de succesvolle bioscoopfilm De nieuwe wildernis en de uitgebreide driedelige gelijknamige VARA-serie die deze maand op televisie was. Prinses Irene is oprichtster van het NatuurCollege. Matthijs Schouten vraagt haar onder meer wat de betekenis van de natuur is, of we ervan vervreemd zijn en wat er nodig is voor een duurzame toekomst.
https://www.youtube.com/watch?v=RdOZmR-geek Lars Hein
Lars Hein (1969) is persoonlijk hoogleraar Ecosystem services and environmental change aan de Universiteit van Wageningen. Zijn onderzoek richt zich op de integratie van milieuwetenschap en milieu-economie, waarbij hij zich vooral focust op 'ecosystem accounting', een nieuwe methode voor het meten van natuurlijk kapitaal. 'Met deze methode kunnen we veranderingen in natuurlijk kapitaal vergelijken met economische statistieken zoals bijvoorbeeld het bruto nationaal product', aldus Hein. Een overzicht
Natural capital accounting | Lars Hein | TEDxWageningenUniversity Natural capital accounting | Lars Hein | TEDxWageningenUniversity van alle projecten waarbij hij betrokken is kan je hier vinden. Bekijk hieronder een video waarin hij zijn onderzoek nader toelicht.
http://www.denieuwewildernis.nl/ https://www.vpro.nl/programmas/tegenlicht/lees/bijlagen/2017-2018/Hoe-duur-is-natuur/De-natuurdenkers.html Naast prinses Irene spreekt Schouten met bioloog Frans Vera, journaliste Tracy Metz, de fotografen Frans Lanting en Sacha de Boer, filosoof Bas Haring en astronaut André Kuipers.
https://app.nlziet.nl/vod/vxgR5K_EUW_8BrZqfczKg
Aculea, de Vlaamse club van bijen- en wespenliefhebbers, presenteert een aantal online opleidingen voor het herkennen van wilde bijen in het veld. Deze opleidingen zijn bedoeld voor de iets verder gevorderde liefhebber, die al enige kennis heeft maar deze graag verder wil verdiepen.
Many of us have been using “Observation Fields” to capture the information that is now (or in the future might be) available in the “Evidence of Presence” annotation. One of the fields I use most frequently is “How was this Detected?” I use this whenever I have an observation that does not depict a complete organism. Since this field has been in use for many years, the frequency with which each of its options is used can be a guide as to which of these options should/could be available in the “Evidence of Presence” annotation.
How was this Detected?
Found Remains (used in 24,084 observations)
Track/Sign (6,272)
Scat (3,978)
Found Feather/Fur/Moult (1,691)
Found Nest (1,479)
Observation by Sight (1,278)
Observation by Sound (408)
Evidence of Feeding (319)
Scratching/Scent Post (113)
Observation by Smell (2)
Mokumers Johnny en Willy („Een boek met een open einde”) spelen. Alleen al de parade aan foute overhemden, colberts en giletjes maken het kijken naar de serie tot een bijzondere belevenis. Net als de scènes uit een huwelijk van Jantje van Amsterdam en zijn Hermien. Bij klachten van haar over hem slaat hij de muur kapot (de deuren zijn al gesneuveld), kan ze „opkankeren” of „een of andere bijgoochem zoeken”.
Hoeren, snoeren, gekkigheid
Ondanks alle gruwelijkheid gaat de kijker een beetje van de karakters houden. Hopelijk biedt de rest van de serie nog meer scènes die korter op het heden zitten. Deel één bood al wat zicht op de blues waarin de mannen terecht zijn gekomen. Het talent om geld uit te geven blijkt nog groter te zijn geweest dan het talent om het te verdienen. „Hoeren, snoeren, gekkigheid, zuipen, snuiven”, somt Dikke Bob op. Van de branie van Jantje van Amsterdam lijkt weinig meer over.
Coming here a bit late, but note that if you want to get a request body from hub.toolforge.org, you can set format=json in the querystring, and get the Wikipedia article URL in the response body at .destination.url. Example: https://hub.toolforge.org/P3151:506262?lang=en&format=json
Moreover, in case there is no article in Wikipedia for the desired language, the URL will be one of another Wikimedia project in the requested language, if available. Example: https://hub.toolforge.org/P3151:506262?lang=en&format=json
The way data gets cached in Android is different than how it works in iOS. In Android, we clear out the app’s local cache of observation photos taken inside the app every time “My Observations” gets loaded and you have an Internet connection, which is pretty frequently. What this means is that we delete the full-size image file the app was holding on to and replace it with a cached version of a smaller version of the image from the website.
That image cache might be filling up, but adding a button to clear it out in the Android would be kind of redundant b/c the operating system already provides a way to clear out an app’s cache. For those of you for whom the Android app is using a ton of space (2+ GB?!), does clearing the app’s cache using that method reduce the disk usage (be careful to clear the cache and not the “storage” or I think it will equivalent to signing out)? If that does drastically reduce the amount of space used, is there really a need to implement a “clear cache” button in the app? IMO, an in-app setting to limit the size of the cache might still be useful, but it’s not clear to me from this thread whether people are asking for / voting for a limit or a “clear cache” optio
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. We call this approach a “leaf model.” :fallen_leaf::robot:
Off the top of my head, some things we’ve taken from previous iNaturalist and other vision challenges include label smoothing, the Xception architecture, changes to how we generate our data exports & minimum number of images for each class, etc. Sometimes however contest winners have done things that we probably won’t do, like training on validation/test data (seems risky for a production model but perhaps worth it to win a contest) or training on larger image sizes (our models already take a long time to train).
The GPU does the lion’s share of the work in computer vision training, and the GPU we used (an NVIDIA RTX 8000) cost more than the rest of the PC put together.
Happily, NVIDIA is a supporter of Cal Academy of Sciences and iNaturali
Kotlin UI Tests (#1088)
As of 51a5077 we're no longer using Lanczos resizing, but @pleary has done some work to suggest the current model gets the best results with images scaled using nearest neighbor resampling, and I think we're using bilinear, so let's switch to nearest neighbor when scaling images before submitting them for CV suggestions. I'm pretty sure this just means using Bitmap.createScaledBitmap(resizedBitmap, newWidth, newHeight, false)
https://forum.inaturalist.org/search?q=elastic Good to know, @maxlath. Our current approach is working for us right now, and we haven't heard from anyone at hub.toolforge.org suggesting that we're sending them too much traffic, but if any of those things should change, we can use your suggestions to start caching the responses.
https://forum.inaturalist.org/t/how-to-create-project-for-a-watershed-knowing-its-usgs-huc-code/9349/15 It’s possible, but maybe not performative. Polygon queries in the database (PostGIS) are generally too slow for us to support (fine when you have a couple thousand records and a few simultaneous connections, not fine with you have a couple million records and a lot of simultaneous connections). Polygon queries in our search index are doable, but I think we’d have to do some thorough testing of the performance implications, and I’m pretty sure precision would be an issue (i.e. the boundaries of the polygon would be considered to be a bit fuzzy). Currently queries for observations in places work by storing the IDs of all the places that contain the obs coordinates in the search index (“what polygons contain this point” is a pretty fast database operation) and then when you ask for “observations in Moldova” or something, we pull all the observations that were indexed with the place ID of Moldova, which is very fast, since there are no geometric operations being performed. The performance problems that come with this approach are that every time you add, delete, or change a place boundary, we need to re-index all the observations that were in the old boundary and all the ones that are in the new one, which takes a long time if that place is Texas. Actually performing a geometric operation in the search index would mean less index churn, but probably slower queries.
search through places in iNaturalist to make sure a similar place doesn’t already exist. you can search by name at https://www.inaturalist.org/places. alternatively, go to the Explore page, zoom into an area on the map that roughly coincides with your watershed boundaries, and click the Places of Interest button to see if there are any places that encompass or are nearby this area. if an existing place doesn’t already exist, go to the next step. (if the place already exists, skip to the last step.)
back at the Server Connections pop-up, select your new connection, and click the Connect button. this brings up a list of layers on the server. in this case you’ll select 17, and click add. that will add the layer to your project.
go to Layer > Open Attribute Table. in the new window, click the Select/Filter Features using form button (or ctrl+F). enter 02030105130 in HUC11 box (or Lawrence Brook in the W_NAME box), and then click Select Features. close the window.
back at the project window, your feature should now be selected. go to Edit > Copy Features. then click Edit > Paste Features as > New Vector Layer.
in the Save Vector Layers as box, select KML as your format. then click on the […] button next to the File Name field. Choose a path on your local machine, and provide a file name of your choosing. click OK.
you can close QGIS at this point.
you now have a KML that you can load into iNaturalist. go to the places page and click on the the Add a New Place button (available only to users with at least 50 verifiable observations, i believe).
in the Create a Place screen, provide a descriptive name, and select your KML file. add a parent if it exists, and select a place type, if you like. then save your place. you now have a new place.
now go to your project (or create one if you haven’t already), and use this new place in your project setup.
Off the top of my head, some things we’ve taken from previous iNaturalist and other vision challenges include label smoothing, the Xception architecture, changes to how we generate our data exports & minimum number of images for each class, etc. Sometimes however contest winners have done things that we probably won’t do, like training on validation/test data (seems risky for a production model but perhaps worth it to win a contest) or training on larger image sizes (our models already take a long time to train).
Yep, a single model. We’ve considered stacked and split models, but we haven’t seen evidence that they are any better than a single monolithic model, so we’ve stuck with the simple approach. Happy to be corrected if anyone’s seen or done research that points in another direction!
Yep, a single model. We’ve considered stacked and split models, but we haven’t seen evidence that they are any better than a single monolithic model, so we’ve stuck with the simple approach. Happy to be corrected if anyone’s seen or done research that points in another direction!
I haven’t experimented with transformers, but after their strong showing at the 2021 iNat Challenge (and many other vision challenges), I’ll certainly take a look.
ik kan de vraag beantwoorden voor het europese model welke nu getraind wordt:
om als soort opgenomen te kunnen worden moet
de taxonomische boom kloppen
minimaal 10 waarnemingen bestaan met 1 of meer fotos welke handmatig gevalideerd zijn met een groen vinkje binnen Europa
de foto`s moeten minimaal 400*400 pixels zijn
het maximaal aantal fotos voor 1 soort is 25.000
https://www.vogelwarte.ch/assets/files/projekte/entwicklung/zustandsbericht%202021/Zustandsbericht%202021_en_low.pdf The annual publication “The State of Birds in Switzerland” (in English, French, German and Italian) summarises the results of various monitoring projects, conducted with the support of more than 2,000 volunteers in all parts of the country. The 2021 report focuses on EBBA2 and its implications for Switzerland. It also takes a closer look at trends in scarce breeding birds like Western Yellow Wagtail, rare passage migrants such as Glossy Ibis, and local winter visitors such as Whooper Swan. You can also explore interactive graphics from the Swiss Bird Index SBI® and the breeding bird index for each species until 2020
Publicado el agosto 1, 2021 06:49 TARDE
por ahospers
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