With new technologies revolutionizing data collection, wildlife researchers are becoming increasingly able to collect data at much higher volumes than ever before. Now we are facing the challenges of putting this information to use, bringing the science of big data into the conservation arena. With the help of machine learning tools, this area holds immense potential for conservation practices. The applications range from online trafficking alerts to species-specific early warning systems to efficient movement and biodiversity monitoring and beyond.
However, the process of building effective machine learning tools depends upon large amounts of standardized training data, and conservationists currently lack an established system for standardization. How to best develop such a system and incentivize data sharing are questions at the forefront of this work. There are currently multiple AI-based conservation initiatives, including Wildlife Insights and WildBook, that are pioneering applications on this front.
This group is the perfect place to ask all your AI-related questions, no matter your skill level or previous familiarity! You'll find resources, meet other members with similar questions and experts who can answer them, and engage in exciting collaborative opportunities together.
Just getting started with AI in conservation? Check out our introduction tutorial, How Do I Train My First Machine Learning Model? with Daniel Situnayake, and our Virtual Meetup on Big Data. If you're coming from the more technical side of AI/ML, Sara Beery runs an AI for Conservation slack channel that might be of interest. Message her for an invite.
Header Image: Dr Claire Burke / @CBurkeSci
Explore the Basics: AI
Understanding the possibilities for incorporating new technology into your work can feel overwhelming. With so many tools available, so many resources to keep up with, and so many innovative projects happening around the world and in our community, it's easy to lose sight of how and why these new technologies matter, and how they can be practically applied to your projects.
Machine learning has huge potential in conservation tech, and its applications are growing every day! But the tradeoff of that potential is a big learning curve - or so it seems to those starting out with this powerful tool!
To help you explore the potential of AI (and prepare for some of our upcoming AI-themed events!), we've compiled simple, key resources, conversations, and videos to highlight the possibilities:
Three Resources for Beginners:
- Everything I know about Machine Learning and Camera Traps, Dan Morris | Resource library, camera traps, machine learning
- Using Computer Vision to Protect Endangered Species, Kasim Rafiq | Machine learning, data analysis, big cats
- Resource: WildID | WildID
Three Forum Threads for Beginners:
- I made an open-source tool to help you sort camera trap images | Petar Gyurov, Camera Traps
- Batch / Automated Cloud Processing | Chris Nicolas, Acoustic Monitoring
- Looking for help with camera trapping for Jaguars: Software for species ID and database building | Carmina Gutierrez, AI for Conservation
Three Tutorials for Beginners:
- How do I get started using machine learning for my camera traps? | Sara Beery, Tech Tutors
- How do I train my first machine learning model? | Daniel Situnayake, Tech Tutors
- Big Data in Conservation | Dave Thau, Dan Morris, Sarah Davidson, Virtual Meetups
Want to know more about AI, or have your specific machine learning questions answered by experts in the WILDLABS community? Make sure you join the conversation in our AI for Conservation group!
I help conservation scientists spend less time on boring stuff.
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I've been working in IT for the past four years and Cybersecurity for the past year and a half. I'm looking to leverage my technical skills towards conservation purposes. I'm new on this journey and excited to jump of volunteer activities where I'm able!
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- @Riley
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I'm a Data Scientist at Western EcoSystems Technology. I am interested in AI processing and statistical modeling of acoustic data and camera trap and drone imagery.
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- @CathyNj
- | She
Catherine Njore is a seasoned Cartographer with over 17yrs experience and specializing in children cartography. She recently designed a Cartography: Fun with Maps Program(CFMP); a program that assists children to learn how to draw, read and use maps effectively.
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- @capreolus
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Capreolus e.U.
wildlife biologist with capreolus.at
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- @volkankorkmaz
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I have been working at the Underwater Association , to protect nature since 94 . Since 1992, I have been a PADI diving instructor
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- @tmcgrath
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Geographer, Program Manager, Engineering Manager
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- @derekrisch
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I'm a conservation ecologist working on invasive mammalian species. Use a variety of monitoring methods which provide an enormous amount of data (yay!) but require a lot of effort to process (nay!). Love keeping up to date on newest tech.
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- @Mumonkan
- | he / him
Wild Me
Software Engineer for Wildlife Conservation
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Wildlife Conservation Society (WCS)
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18 month postdoc research position, Netherlands, EU-funded
28 March 2024
Article
You’re invited to the WILDLABS Variety Hour, a monthly event that connects you to conservation tech's most exciting projects, research, and ideas. We can't wait to bring you a whole new season of speakers and...
22 March 2024
Join our multi-national team at the AI for Biodiversity Change Global Climate Center! We're hiring a Research Data Manager & Tech Coordinator at Ohio State. Support cutting-edge research on climate change &...
15 March 2024
Catch up on the conservation tech discussions and events that happened during World Wildlife Day 2024!
7 March 2024
EcoAssist introduces a free African species identification model for camera trap images, capable of recognising 30 species.
5 March 2024
Join us to help prevent biodiversity loss! Understory is hiring a postdoc to lead R&D Development on generalizing Computer Vision models for vegetation identification across space/time/phenotypes.
29 February 2024
Join the Luxembourg Institute of Science and Technology (LIST) in pioneering environmental and ecological monitoring! 🌍💡 As part of ERIN’s Observatory for Climate, Environment, and Biodiversity (OCEB), you'll be at the...
26 February 2024
SNTech are recruiting for 3 roles to assist us to develop computer vision pipelines for underwater monitoring
15 February 2024
We invite applications for the third Computer Vision for Ecology (CV4E) workshop, a three-week hands-on intensive course in CV targeted at graduate students, postdocs, early faculty, and junior researchers in Ecology...
12 February 2024
The primary focus of the research is to explore how red deer movements, space use, habitat selection and foraging behaviour change during the wolf recolonization process.
10 February 2024
Applications open for a PhD position in plant vibroacoustics at the University of Southampton
8 February 2024
We demonstrate the power of using passive acoustic monitoring & machine learning to survey species, using ruffed lemurs in southeastern Madagascar as an example.
23 January 2024
April 2024
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March 2024
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February 2024
Description | Activity | Replies | Groups | Updated |
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Dear Community,Together with Hackster.io, Seeed Studio is very happy to jointly organize “IoT Into the Wild Contest for Sustainable Plant... |
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AI for Conservation, Connectivity, Emerging Tech, Open Source Solutions, Sensors | 1 year 9 months ago | |
Thanks Carly. No special areas of interest for now although that will happen over time. Thanks so much for your reply. I will check the Conservation Tech directory out. Soumya |
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AI for Conservation | 1 year 9 months ago | |
Fascinating article, combining machine learning and acoustical signals to correlate coral reef health.https://www.sciencedirect.com/science... |
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Acoustics, AI for Conservation, Marine Conservation | 1 year 9 months ago | |
We've now wrapped our first run of AI for Conservation Office Hours and you can read my review of how it went and lessons learned here. Given the ... |
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AI for Conservation | 2 years 3 months ago | |
Hi everyone! We are spreading the word about a free, open-source tool called Zamba that automatically detects and... |
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AI for Conservation | 2 years 4 months ago | |
Hi Wildlabbers, This week's Tech Tutor Jamie MacAulay is talking about how to use and analyze large acoustic data using... |
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Acoustics, AI for Conservation, Marine Conservation | 2 years 5 months ago | |
Hi Wildlabbers, We're getting ready for tomorrow's episode with Tech Tutor Lily Xu, who'll talk to us about how machine... |
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AI for Conservation, Protected Area Management Tools, Wildlife Crime | 2 years 6 months ago | |
Looks good, but what is the added value compared to other examples as Obsidentify and Plantnet? |
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AI for Conservation | 2 years 7 months ago | |
https://www.dryad.netJob description"Dryad is an environmental IoT startup based in Berlin-Brandenburg. Our mission is to develop a large-... |
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AI for Conservation | 2 years 7 months ago | |
Deep Learning Engineer at Pachama - https://jobs.lever.co/pachama/81716dd9-8019-4916-add2-fcfaae426331 Embedded Software Engineer... |
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AI for Conservation | 2 years 7 months ago | |
Hi everyone, We're excited to welcome Nicole Flores to Tech Tutors to walk us through getting started with Wildlife Insights! ... |
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AI for Conservation, Camera Traps, Data management and processing tools | 2 years 8 months ago | |
Hi all, We're excited to welcome Siyu Yang to Tech Tutors to chat about getting started with Megadetector! For all you AI... |
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AI for Conservation, Camera Traps, Data management and processing tools | 2 years 8 months ago |
ibm-nasa-geospatial (IBM NASA Geospatial)
28 March 2024 9:22am
NASA and IBM have teamed up to create an AI Foundation Model for Earth Observations, using large-scale satellite and remote sensing data, including the Harmonized Landsat and Sentinel-2 (HLS) data.
Applying Open-Source AI to Camera Trap Imagery
27 March 2024 4:34pm
AI for Conservation!
4 March 2024 8:51pm
22 March 2024 5:57pm
Thank you for the tip! I'll definitely consider contributing to open source projects and taking part in challenges :)
25 March 2024 5:22am
We could always use more contributors in open source projects. In most open source companies Red Hat, Anaconda, Red Hat and Mozilla, people often ended up getting hired largely due to their contributions on open source projects. These contributions were both technical such as writing computer code and non-technical such as writing documentation and translating tools in their local language.
The Variety Hour: 2024 Lineup
22 March 2024 4:30pm
The Variety Hour: March 2024
21 March 2024 7:39pm
21 March 2024 9:48pm
SLN Webinar: Tech for wildlife: The role AI and technology can play in nature conservation
18 March 2024 9:17am
BirdWeather | PUC
27 October 2023 7:45pm
2 November 2023 9:20pm
I love the live-stream pin feature!
14 March 2024 10:29pm
Hi Tim, I just discovered your great little device and about to use it for the first time this weekend. Would love to be directly in touch since we are testing it out as an option to recommend to our clients :) Love that it includes Australian birds! Cheers Debbie
16 March 2024 10:47pm
Hi @timbirdweather I've now got them up and running and winding how I can provide feedback on species ID to improve the accuracy over time. It would be really powerful to have a confirmation capability when looking at the soundscape options to confirm which of the potential species it actually is or confirm it is neither to help develop the algorithms.
Also, is it possible to connect the PUC to a mobile hotspot to gather data for device that isn't close to wifi? And have it so that it can detect either wifi or hotspot when in range? Thanks!
Data Manager and Technology Coordinator, ABC Global Climate Center
15 March 2024 5:01pm
The Freshwater Sounds Archive
15 March 2024 10:32am
Introducing The Freshwater Sounds Archive, a global database of sounds produced by freshwater species.
Submit your species-specific or unidentified sounds to the archive now and receive recognition for your contribution in a forthcoming data paper as a co-author!
Free AI Camera Trap Model for European Fauna!
12 March 2024 12:33pm
EcoAssist has now incorporated the Deepfaune v1.1 species identification model for camera trap images, capable of recognizing 26 European species. The model is developed by Deepfaune initiative. More information is available at: https://www.deepfaune.cnrs.fr/.
Labelled Terrestrial Acoustic Datasets
16 February 2024 10:24pm
8 March 2024 11:54pm
Thanks for sharing Kim.
We're using <1 mA while processing, equating to ~9 Ah running for a year. The battery is a Tadiran TL-5920 C 3.6V Lithium, providing 8.6 Ah, plus we will a small (optional) solar panel. We also plan to implement a threshold system, in which the system is asleep until noise level crosses a certain threshold and wakes up.
The low-power MCU we are using is https://ambiq.com/apollo4/ which has a built-in low power listening capability.
9 March 2024 6:25am
<1 mA certainly sounds like a breakthrough for this kind of device. I hope you are able to report back with some real world performance information about your project @jcturn3 . Sounds very promising. Will the device run directly off the optional solar cell or will you include a capacitor since you cannot recharge the lithium thionyl chloride cell. I had trouble obtaining the Tadarian TL-5920 cells in Australia (they would send me old SL-2770s though) so I took a gamble on a couple of brands of Chinese cells (EVE and FANSO) which seemed to perform the same job without a hitch. Maybe in the USA you can get Israeli cells more easily than Chinese ones?
Message me if you think some feeding sounds, snoring, grooming and heart sounds of koalas would be any use for your model training.
9 March 2024 7:01am
Really interesting project. Interesting chip set you found. With up to around 2mb sram that’s quite a high memory for a ultra low power soc I think.
It might also be interesting while doing your research thinking about if there are any other requirements people could have for such a platform with a view towards more mass usage later. Thanks for sharing.
Here's what you missed at World Wildlife Day 2024
7 March 2024 9:02pm
15 March 2024 2:42pm
EcoAssist - Free African species identification model for 30 species!
5 March 2024 5:10pm
Machine Learning Postdoc Position, Understory
29 February 2024 11:56pm
Successfully integrated deepfaune into video alerting system
2 December 2023 11:15am
29 February 2024 9:41am
As I understand it, the deepfaune's first pass is an object detector was based on megadetector, @schamaille could explain it exactly. In short though, it's output is standard yolo like in terms of properties. From this I use standard opencv code to snip out the individual matches and pass them to the second stage, which is a classifier.
My code needs a bit of cleaning up before I can release it, also it needs to be made more robust for some situations. Also, I'm waiting to hear if I got anywhere with wildlab awards as it would affect my plans going forward. And this could be anything up till the end of next month, though at a wild guessing I'm guessing next week at the UN WWD or at the wildlabs get together :) Anyone else have any theories ?
Also, my code is a little more complex because I abstract the interface to a network based API.
Finally, I don't want to take the wind out of my sails, I would like to launch my integration in time with the release of the Orin based version of my StalkedByTheState software, the usage of which I'm trying to promote. To release earlier take's some of the oomph out of this.
But maybe we can have a video call sometime and we can have a chat about this?
29 February 2024 10:36am
In the DeepFaune final paper, it's mentioned that the team developed their own observation type model (detector) based on YOLOv8s, utilizing the cropping information provided by MegaDetectorV5a.
Therefore, for the initial phase, I'm also utilizing the YOLO interface (from Ultralytics) to load the deepfaune-yolov8s_960.pt model and perform the prediction procedure. The results list contains one or more bounding boxes with class ID (animal, person, vehicle) and probability values.
For each object detection, I crop and resize the original image to the area of the bounding box, execute the preprocessImage transformation, and utilize the predictOnBatch method (both from the Classifier class which load deepfaune-vit_large_patch14_dinov2.lvd142m.pt in the background) to obtain scores for species-level classification for each individual bounding box.
This approach could prove valuable to other users seeking to integrate two-step DeepFaune detection and classification into their pipelines or APIs.
29 February 2024 11:04am
Absolutely! I pretty much do the same thing, the resizing step I think relates to what I still have to do. Some large images caused my code to crash.
I want to take it one step further, and that's one of the reasons I want to talk to Microsoft about, I'd like to encourage the abstraction of the object detection with the network API approach I developed as that would mean that any new models anyone developed would simply work out of the box with no additional work with my video alerting software. To that end I need to have a chat to see if they agree with the added value, if so they could potentially add this wrapper around their code and all of those models would be available to alert on and to use is simple Python scripts in other peoples pipelines.
Anyway. That's the plan.
Pytorch-Wildlife: A Collaborative Deep Learning Framework for Conservation (v1.0)
21 February 2024 10:30pm
25 February 2024 2:15am
Thanks Dan! I did actually, after giving up using PyTorch and it was amazing!
26 February 2024 7:38pm
Hello @hjayanto , You are precisely the kind of collaborator we are looking to work with closely to enhance the user-friendliness of Pytorch-Wildlife in our upcoming updates. Please feel free to send us any feedbacks either through the Github issue or here! We aim to make Pytorch-Wildlife more accessible to individuals with limited to no engineering experience. Currently, we have a Huggingface demo UI (https://huggingface.co/spaces/AndresHdzC/pytorch-wildlife) to showcase the existing functionalities in Pytorch-Wildlife. Please let us know if you encounter any issues while using the demo. We are also in the process of preparing a tutorial for those interested in Pytorch-Wildlife. We will keep you updated on this!
26 February 2024 11:58pm
This is great, thank you so much @zhongqimiao ! I will check it out and looking forward for the upcoming tutorial!
Engineer in novel technologies and approaches for biodiversity monitoring
26 February 2024 6:12pm
Needing help from the community: Bioacoustics survey
14 February 2024 9:46am
24 February 2024 7:23pm
Was great to chat with you Sofia and I would encourage others in the Acoustics community to help provide input for Sofia's study!
26 February 2024 8:57am
Thank you so much for your encouraging words! I'm thrilled to hear that you enjoyed our conversation, and I truly appreciate your support in spreading the word about my survey within the Acoustics community. Input from individuals like yourself is incredibly valuable to my study, and I'm eager to gather as much insight as possible. If you know of anyone else who might be interested in participating, please feel free to share the survey link with them. Once again, thank you for your support—it means a lot to me!
Best regards,
Sofia
Tools for automating image augmentation
26 January 2024 2:33pm
16 February 2024 7:42am
Hi @arky !
Thanks for your reply.
I am running into pytorch/torchvision incompatibility issues when trying to run your script.
Which versions are you using?
Best regards,
Lars
18 February 2024 11:05am
@Lars_Holst_Hansen Here is the information you requested. Also run Yolov8 in multiple remote environments without any issues. Perhaps you'll need to use a virtual environment (venv et al) or conda to remedy incompatibility issues.
$ yolo checks
Ultralytics YOLOv8.1.4 🚀 Python-3.10.12 torch-1.13.1+cu117 CUDA:0 (Quadro T2000, 3904MiB)
Setup complete ✅ (16 CPUs, 62.5 GB RAM, 465.0/467.9 GB disk)
OS Linux-6.5.0-17-generic-x86_64-with-glibc2.35
Environment Linux
Python 3.10.12
Install pip
RAM 62.54 GB
CPU Intel Core(TM) i7-10875H 2.30GHz
CUDA 11.7
matplotlib ✅ 3.5.1>=3.3.0
numpy ✅ 1.26.3>=1.22.2
opencv-python ✅ 4.7.0.72>=4.6.0
pillow ✅ 10.2.0>=7.1.2
pyyaml ✅ 6.0.1>=5.3.1
requests ✅ 2.31.0>=2.23.0
scipy ✅ 1.11.4>=1.4.1
torch ✅ 1.13.1>=1.8.0
torchvision ✅ 0.14.1>=0.9.0
tqdm ✅ 4.66.1>=4.64.0
psutil ✅ 5.9.8
py-cpuinfo ✅ 9.0.0
thop ✅ 0.1.1-2209072238>=0.1.1
pandas ✅ 1.5.3>=1.1.4
seaborn ✅ 0.12.2>=0.11.0
18 February 2024 11:18am
Perfect thanks! I am still a novice using Python but my wife can help me!
3x Ai 4 Conservation Job Roles (UK)
15 February 2024 3:28pm
Exploring an ethical reflection tool for animal-focused tech (Survey)
13 February 2024 8:22pm
Mass Detection of Wildlife Snares Using Airborne Synthetic Radar
7 January 2024 6:50am
10 February 2024 1:32pm
Operating at 2GHz the radar penetrates vegetation so could see through canopy, but not through trunks of trees. However snares are typically set in groups, so one could maximise chance of locating all snares by carrying out a circular/spiral flight path after detection of a potential snare to locate others
12 February 2024 12:12pm
Hi David,
I assume this will only work with wire (metal) snares? We often see snares made of nylon rope (used for lucern bales) in the field, which I assume will be missed by the radar?
Cheers,
Chavoux
13 February 2024 8:43am
Hi David, would love to collaborate with you on this topic. A few years ago Dr. Nick van Doormaal did his PhD on snaring with us and we ran a number of experiments on the detection of snares in a real world scenario using trained anti-poaching teams. I think it would be quite simple to replicate the study and then look at the efficacy of remote sensing vs human detection. Let me know if you are interested in chatting further!
Computer Vision for Ecology Workshop 2025 Call for Applications
12 February 2024 9:29pm
ChatGPT for conservation
16 January 2023 10:04am
4 February 2024 9:28am
The greatest issue with ChatGPT is GIGO (Garbage in, garbage out). It doesn't matter how good the machine learning algorithm is, if it gets fed bad information (data) it will regurgitate bad information. One obvious problem is that it does not reference its information sources. So some of it might be established beyond any doubt, but then it includes something it made up out of thin air with an equally authoritative tone. Because at bottom, ChatGPT is still a dumb machine (or collection of machines) that has to be told what to do by its programmers. It can be useful, but for conservation issues that can have far-reaching implications, I will not trust it. It could be really useful with the addition of two measures (maybe one has already been implemented?):
- The option to show the references for all sources (for each statement that it makes; and if it makes its own logical deduction, show that explicitly).
- Either weighing or restricting its input to sources that has been checked (e.g. peer-reviewed articles) for at least its scientific output (maybe/hopefully Google is already doing this).
I think with the addition of these two functions it will really become useful to conservation. But we are not there yet. In the meantime it is similar to Wikipedia, maybe a good a starting point for further research.
4 February 2024 5:39pm
Just so you know, I uploaded both a photo without a cat and one with a cat in the picture and ask if there was a cat in the picture it got it correct both times.
Uploading pictures to wildlabs doesn't seem to work at this time, so I can't show you the response, but the second answer with the cat in the picture it answered with:
"Yes, there is a cat in this picture. It appears to be in the middle of the driveway."
12 February 2024 1:05pm
You can already achieve both of them with your prompt.
Or, if you're not using ChatGPT specifically but another LLM that you can fine tune, you can use RAG or fine tuning to extra train the algorithm on the data you want it to extract information from.
With ChatGPT you can create your custom GPT now.
Post-doc possition - Field spanning movement ecology, ecology of fear, bio-logging science, behavioral ecology, and ecological statistics
10 February 2024 7:20am
Apply Now: UW Data Science for Social Good Projects
8 February 2024 6:45pm
Sign up for Data Science for Social Good 2024! This summer program is a great opportunity to get dedicated data science support on a conservation (tech) project or to get rich experience as a student in the field. More info in the link - student apps due 2/12, projects due 2/20.
PhD Opportunity - Exploring plants’ sensing capability with vibroacoustics
8 February 2024 5:35pm
Southern African Wildlife Management Association Conference 2024
6 February 2024 12:20pm
22 March 2024 12:29pm
Welcome, Have you considered participating in any of the AI for Good challenges. I find it is good way to build a nice portfolio of work. Also contributing to existing open source ML projects such as megadetector or to upstream libraries such as PyTorch is good way to getting hired.