←Back to Beyond Market Intelligence
•2 min read•from Machine Learning

U-Net for Agricultural Field Segmentation [P]

Our take

Hello everyone! I’m currently working on a solo project focused on agricultural field analytics using a U-Net architecture enhanced with an attention mechanism. My model was trained on the AI4Boundaries dataset, but I’m facing challenges when switching to raw Sentinel-2 data, leading to a significant drop in confidence. I’m exploring whether stacking images from different dates could help mitigate noise and cloud interference, and I’d appreciate any insights on handling varying sun and viewing angles.
U-Net for Agricultural Field Segmentation [P]
U-Net for Agricultural Field Segmentation [P]

Hi everyone, I’m working on a solo student project (it was supposed to be a team of five, but here I am) focused on agricultural field analytics.
Architecture: U-Net with an attention mechanism
Data: Trained on the AI4Boundaries dataset (5 channels)

The problem: When I switch to raw Sentinel-2 data, the model’s confidence drops to almost zero.

Questions:
Should I stack images from different dates to reduce noise and cloud interference?
How should I handle varying sun and viewing angles that are not present in the training set?
How can I improve the model’s performance when the training data differs significantly from the real-world data?

Any advice on making the model more robust for real-world conditions would be appreciated.

P.S. I’ve been coding for the last 12 hours and have already started drinking just to avoid looking at this mess again, so I might have missed some community rules. If needed, I can share the full code , it’s all public.

Training:

https://preview.redd.it/2u0vgg3tpeyg1.png?width=1462&format=png&auto=webp&s=7e8f773bddfc218955f931813c423e3b22ed1e6d

Real:

https://preview.redd.it/irlpf6alpeyg1.png?width=959&format=png&auto=webp&s=8da6955b9b5c73f5d9e49e6e29b27d70125109d9

submitted by /u/niki88851
[link] [comments]

Read on the original site

Open the publisher's page for the full experience

View original article →

Tagged with

#generative AI for data analysis#Excel alternatives for data analysis#real-time data collaboration#big data performance#big data management in spreadsheets#conversational data analysis#intelligent data visualization#data visualization tools#enterprise data management#data analysis tools#data cleaning solutions#natural language processing for spreadsheets#real-time collaboration#rows.com#self-service analytics tools#large dataset processing#row zero#cloud-based spreadsheet applications#financial modeling with spreadsheets#no-code spreadsheet solutions
U-Net for Agricultural Field Segmentation [P] | Beyond Market Intelligence