The Eden Library Viewer is capable of detecting apple threats in real-time during spraying applications!
Visit our website to learn more!
https://t.co/xLFY5kNsSI
#edenlibrary#cropmonitoring#agtech#cropprotection
Our second eBook "Agtech: A use case specific domain" is out! 📕
In our new eBook, we present three completely different agricultural environments with specific vision-based use cases.
https://t.co/8ryDaOAn9y 📥
Enjoy!
#edenlibrary
We are committed to help farmers automate crop inspection tasks and reduce chemical cost, by simply mounting on their tractor the #Viewer device and obtain critical information from every field pass. 👨🌾
Learn more about our device: https://t.co/oeTaJa5PNv
#edenlibrary
A small demonstration of our "Viewer" device in collaboration with the Agricultural Cooperative of Kastoria.
Visit our website to learn more about our Viewer!
https://t.co/oeTaJa5PNv
#edenlibrary#edenlibraryviewer#ai#cropprotection#agtech
Our library hosts #UAV image datasets of grape vine and tomato including #RGB, #thermal and #monochromatic types of images, ideal for more advanced computer vision projects!
Explore our premium #datasets & start your #AI project now!
👉 https://t.co/JZHY9KslXX
#edenlibrary
Excited to team up with @agROBOfood for the upcoming webinar "Artificial Intelligence and Image Processing in Agriculture", where we will share insights based on our field experience.
Register now!
👉 https://t.co/wcOOV6HrhD
📅 27.05.22
🕐 10:00-11:00 CEST
#webinar#ai#agtech
@Eden_Library_AI & @SmartFarmingTechnologyGroup developed a camera-based system for#crop #monitoring and #smart#spraying 👏🏻👏🏻
#edenlibrary Viewer is officially launched 🚀
Get to know it 🏃♂️ 💡
https://t.co/TwoD6D86PX
Image collection & disease detection is a laborious task requiring proper tree marking.
In the Viewer device, we've developed a YOLO_V5 #AI model from @Ultralytics that automatically detects markers, increasing the attention on diseased trees & improving symptoms inspection.
Want to bring annotation time to the minimum?
Watch our latest tutorial and learn how to avoid laborious time spent on annotation tasks!
You can download our datasets here:
https://t.co/jkOjo4Dhmj
#edenlibrary#tutorial#ai#annotation#agritech#deeplearning
Our library is constantly updated with new image datasets of premium quality.
Check few of our premium datasets of orange tree, grape vine, cotton etc.
Visit our website to view more!
https://t.co/5jIMFV3qOT
#edenlibrary
Modern vision technologies and AI promise to address the challenge of early disease detection.
Visit Eden Library's annotated images, use your free credits to download your selected dataset and start building your vision application ➡️ https://t.co/LEUCSyqbtP
#edenlibrary
Discover now our new readily annotated image datasets of:
• Multiple Weeds
• Olive tree
• Orange tree
• Pepper
• Tomato
Good news!
We offer your first 50 credits for purchasing your datasets for free!
Sign up now: https://t.co/TumwzDyJte
💡 #elhint
Consistency when annotating is one of the keys to high quality annotations. Therefore, once the annotation process is finished make sure to check a percentage of the annotated images performed by each annotator.
#agrotech#computervision#ai#edenlibrary
Things to consider:
➡️The availability of the crop of interest at the
specific location and time.
➡️The environment in which data will be acquired and the model will be deployed.
➡️The equipment used to capture the data.
➡️ The number of images required per class.
#edenlibrary
New Notebook Alert! 🚨 #edenlibrary
In this notebook, we evaluate different metrics for measuring the similarity between different images and the same image with noise.
Visit our website and check it!
➡️ https://t.co/7HwKeDlShb
#ai#computervision#agritech
Our first eBook "A guide to Computer Vision in Agtech" is out! 📕
Learn why you should care about computer vision in Agtech & read our helpful hints about the data collection & annotation process.
Download it here:
https://t.co/rFYbhrekMI
Enjoy!
#agritech#computervision#ai
#ELHint 💡
Prior to annotating make sure you understand 100%
your specific project needs!
Annotating occluded fruits may be of high value for
estimating yield but useless for robotic harvester
applications if the end-effector is unable to reach them without damaging the crop❕