Wildlife@Home

A Push for UAV Imagery Analysis

We're making a push to analyze recent UAV imagery taken from the Hudson Bay! Help us find birds, bears and caribou in our images collected from an unmanned aircraft (aka. Drone) in Northern Manitoba. The wildlife found in the images will be used to create training datasets for us to automate post-processing of large datasets from aerial imagery.

You can help us by reviewing images for the UAS Estimating Snow Geese project.

Welcome to Wildlife@Home

Wildlife@Home is a joint effort from University of North Dakota's Department of Computer Science and Department of Biology, aimed at analyzing video gathered from various cameras recording wildlife. Currently the project is looking at video of sharp-tailed grouse, Tympanuchus phasianellus to examine their nesting habits and ecology. The nest cameras have been set up up both near western North Dakota's oil fields and also within protected state lands. We recently have also begun studying two federally protected species, interior least terns, Sternula antillarum, and piping plovers, Charadruis melodus.

Wildlife@Home Goals

We hope that your participation will help us determine the impact of the oil development on the sharp-tailed grouse, and better understand the behaviors of least terns and piping plovers to aid in their conservation, as well as provide some interesting video for everyone to watch and discuss.

Each spring we capture hens on the lek or dancing grounds where males display for females. We fit hens with a necklace-style radio transmitter that emits a unique radio frequency which we can use to relocate the bird and find her nest.

We track grouse using radio telemetry receivers and various types of antennas such as this handheld antenna and receiver. Photo courtesy of Chris Felege.

We track grouse using radio telemetry receivers and various type so antennas such as this truck mounted antenna. Photo courtesy of Anna Mattson.

Once we find a nest, we install a miniature surveillance camera near the nest.

Nest cameras are powered by cable, from about 75 feet away with a 12 volt battery and a waterproof box housing a DVR that will record to SD cards.

A sharp-tailed grouse nest.

Hens will incubate a nest for about 23 days unless a predator finds and destroys the nest. This is a snapshot from our nest cameras of hen incubating her nest.

Sharp-tailed grouse chicks hatching.

Various predators such as this Swainson’s Hawk will attack the hen while she is sitting on the nest. This image is from one of our nest cameras.

Ground predators, such as this American Badger, will destroy the nest.

After the peak of hatch, we follow hens with broods via radio signals. Once the chicks are about a month old, we will relocate the brood and catch them in big net during the night. Chicks are then fitted with their own necklace-style radio transmitters so we monitor their survival and reproduction over the next year.

This image found in the collected video shows a lightning crash behind a piping plover incubating a nest on the Missouri River in North Dakota.

This image found in the collected video shows a piping plover chick walking across the video screen with an adult brooding the remaining chicks on the nest in the background.

The leg bands used by wildlife biologists for bird identification are clearly visible on the flying adult piping plover.

A tern chick yawns in front of the camera while the adult tern incubates the remaining egg on the nest. This image was found in the collected video.

Interior least terns exhibit biparental investment in their nests. This image found in the collected video shows a nest exchange event between two flying tern parents.

An adult tern feeds a fish to a tern incubating a nest. This image was found in collected video.

Volunteer Your Computer

Watch Wildlife Videos

Review Wildlife Images

User of the Day

The Dreamer
I am a single Electrical/Computer Engineer currently in Manhattan, Kansas, where I work for Kansas State University as a Senior Unix Systems...

News

[wildlife] two publications accepted to this year's IEEE eScience conference

So we had two papers accepted to the 13th IEEE International Conference on eScience this year! One on EXACT (what you've been crunching) and the other on the unmanned aerial systems imagery you've been marking up. If you'd like to read pre-prints here they are:

Developing a Volunteer Computing Project to Evolve Convolutional Neural Networks and Their Hyperparameters.

Toward Using Citizen Scientists to Drive Automated Ecological Object Detection in Aerial Imagery.

Congrats to Marshall and Connor on their paper!

Travis Desell on Friday, August 18th
leave a comment

[all] min post credit

Hi All,

Since work is flowing pretty much steadily now, to help better deal with spammers I've set a minimum credit limit to post to 1. If this is going to be an issue (and now you can't post), please send me an email.

Also, to create a team a user will also need to have credit.

Hoping this helps!

--Travis

Travis Desell on Wednesday, August 16th
leave a comment

[wildlife] app version 0.32

So I found a bug in the application/assimilator that was causing some server side errors. I'm releasing v0.32 for the application -- unfortunately this is going to cause the workunits currently in the system to immediately error out.

Please feel free to cancel any workunits you're running with v0.31 to not lose any credit from this (alternately if you've already seen your WU has wingmen then it should validate against them). I really apologize but this was the only real fix I had at my disposal.

Travis Desell on Wednesday, August 2nd
leave a comment

[wildlife] back up and running

Everything should be back up and running. Let me know if you're seeing any weird workunits (i.e., really long run times).

I'll also have an application update out tomorrow which should help track down some of those issues and improve reliability.

Travis Desell on Monday, July 24th
leave a comment

[wildlife] assimilator issue

I'm currently debugging an issue with the assimilator. I hope to have things up and running soon.

Travis Desell on Monday, July 24th
leave a comment

[wildlife] new app/type version 0.31 and an update

I've made an update to the application which I'm hoping will allow us to get even better results. Currently we've hit 99.45% on the MNIST dataset, which is actually quite good considering the current version of the application only performs convolutional operations and doesn't do any pooling. Here's a list of some of the best published results on this dataset:

http://rodrigob.github.io/are_we_there_yet/build/classification_datasets_results.html#4d4e495354

And that puts is pretty solidly in the middle of the list. The new application now lets EXACT also evolve CNNs with pooling operations, which I'm hoping will bump us even higher up the list. This is pretty exciting as we're evolving the structure of the convolutional neural networks (CNNs) from scratch, and we're getting competitive with some of the best human designed CNNs. Anywho, let me know if you are having any errors with the new v0.31 applications.

On another note, I just returned from this years Genetic and Evolutionary Computation Conference in Berlin, where I presented a poster on this work. There was quite a bit of interest in this approach so that was really good. I just want to thank everyone again for contributing all your cycles to this work.

Travis Desell on Sunday, July 30th
leave a comment

[wildlife] new runs

I've started up a new set of runs. I made some tweaks to the backend to improve accuracy of how we're storing things in the database (found a couple bugs that while not fatal were not giving me the information I wanted). Workunit names look like:

exact_genome_TIMESTAMP_ID_NUMBER

And in this case, the ID will be >= 39 and <= 43. Let me know if you're having any errors with these new workunits.

On another note, I recently submitted a paper to this years IEEE eScience conference. You can take a look at the preliminary draft here:

http://tdesell.cs.und.edu/papers/2017_escience_exact.pdf

Our results are starting to get quite good. I also have an application update that should improve things even further -- but want to get a few more data points with the current implementation before doing the update.

Travis Desell on Wednesday, July 12th
leave a comment

[wildlife] credit reimbursement and credit rate reduction

Sorry for taking a bit long on this, but I've gone through and done a credit reimbursement for the MNIST app which was having the "monster" workunits. I took everyones credit for that app and multiplied it by 1.15 (i.e., a 15% bonus).

On another credit related note, I've dropped the credit awarded from future generated workunits by 10%, as the general consensus is that the credit rate is really high. Let me know what you think about this and I can do some more adjustment if it was not enough (or too much).

Travis Desell on Wednesday, July 12th
leave a comment

[wildlife] assimilator updates

So it looks like the poor assimilator is struggling under the load of the larger workunits (a good problem to have), which means work generation has been slow. I've made a few updates which I hope will help get things moving faster and more work flowing.

Travis Desell on Tuesday, May 30th
leave a comment

[wildlife] windows xp connection issues

I tried a fix on my end for those who have been having trouble connecting to the server with Windows XP. The scheduler in the header for the main page of csgrid had http://csgrid.org listed for the scheduler instead of https://csgrid.org

Let me know if this fixed anything (or broke anything -- hopefully not)!

Travis Desell on Wednesday, June 7th
leave a comment

Active Projects

Feel free to scroll through our image gallery above to get a better idea of what is going on with the project and see the field biologists in action, talk to us on the message boards, or watch videos about the project on our Google+ YouTube Channel. The following projects are actively being worked on by these Wildlife@Home team members:

Alicia Andes - Refined Monitoring Techniques to Understand Least Tern and Piping Plover Nest Dynamics
Paul Burr - Sharp-tailed Grouse Nest Predation Relative to Gas and Oil Development in North Dakota
Rebecca Eckroad - Nest Cameras and Citizen Science: Implications for evaluating Sharp-tailed Grouse Nesting Ecology
Kyle Goehner - Automated Wildlife Detection in Uncontrolled Environments

Contact Information

Please email any questions or suggestions to Travis Desell, or feel free to post a message in our forums.

The Wildlife@Home team includes:

Travis Desell, Assistant Professor of Computer Science, University of North Dakota
Susan Ellis-Felege, Assistant Professor of Biology, University of North Dakota
Chris Felege, Educational Outreach Coordinator, Instructor of Biology, University of North Dakota
Alicia Andes, Graduate Research Assistant in Biology, University of North Dakota
Connor Bowley, Graduate Research Assistant in Computer Science, University of North Dakota
Nickolas Conrad, Undergraduate Research Assistant in Biology, University of North Dakota
Kyle Goehner, Graduate Research Assistant in Computer Science, University of North Dakota
Marshall Mattingly III, Graduate Research Assistant in Computer Science, University of North Dakota
John Palarski, Undergraduate Research Assistant in Biology, University of North Dakota
Lindsey Wingate, Undergraduate Research Assistant in Computer Science, University of North Dakota

With agency support from:

Kaylan Carrlson, Manager of Conservation Planning, Ducks Unlimited.
Tanner Gue, Conservation Specialist, Ducks Unlimited.
Aaron Robinson, North Dakota Game and Fish.
Terry Shaffer, U.S.G.S. Northern Prairie Wildlife Research Center.
Mark Sherfy, U.S.G.S. Northern Prairie Wildlife Research Center.

With previous support from:

Robert Bergman, Graduate Research Assistant in Computer Science, University of North Dakota
Paul Burr, Graduate Research Assistant in Biology, University of North Dakota
Benjamin Carpenter, Undergraduate Research Assistant in Compute Science, University of North Dakota
Becca Eckroad, Undergraduate Research Assistant in Biology, University of North Dakota
Jaeden Lovin, Undergraduate Research Assistant in Compute Science, University of North Dakota
Adam Pachl, Undergraduate Research Assistant in Biology, University of North Dakota
Julia Johnson, Undergraduate Research Assistant in Biology, University of North Dakota
Nitin Karodiya, Graduate Research Assistant in Computer Science, University of North Dakota
Eric Kjeldergaard, Graduate Research Assistant in Computer Science, University of North Dakota
Leila Mohsenian, Undergraduate Research Assistant in Biology, University of North Dakota
Kelly Sagen, Undergraduate Research Assistant in Biology, University of North Dakota
Rebecca VanderClute, Undergraduate Research Assistant in Computer Science, University of North Dakota

Publications

All publications, talks and posters about DNA@Home can be viewed on the Citizen Science Grid's publications page.

Support

Wildlife@Home is currently being supported by NSF award no. 1319700 through the Division of Intelligent Information Systems's Information Integration and Informatics (III) program.

Wildlife@Home is collaborating with Ducks Unlimited on a project invovling blue winged teal.

Wildlife@Home has been generously supported by a collaborative research award and new faculty SEED grant from UND's Office of Research Development and Compliance. The project's video streaming server is hosted by UND's Computational Research Center and the volunteer computing server is hosted by UND's Scientific Computing Center.

North Dakota Game and Fish has provided financial support for field logistics to collect sharp-tailed grouse videos.

USGS has provided financial support for camera equipment, video storage, and field assistance to collect data for the piping plover and interior least tern.

Wildlife@Home is in part powered by the Berkeley Open Infrastructure for Network Computing (BOINC).