InsectSAM is an open-source machine learning model designed for the Diopsis camera systems and Arise Biodiversity algorithms to monitor insect biodiversity in the Netherlands.

To further our academic non-profit objectives, we are creating a Insect Model Zoo Gradio space where we will compare InsectSAM with other alternatives we have trained, such as Yolo v8 and Detectron2, specifically for insect detection and segmentation. This comparison would utilize GPU compute power to generate predictions, ensuring a robust and thorough evaluation of each model's performance.

How It Solves Environmental Problems:

Accurate Monitoring:

Automates insect segmentation, providing reliable data on insect populations.
Reduces manual analysis time and human error.

Ecosystem Health:

Insects are key indicators of ecosystem health. Monitoring them provides insights into environmental conditions.
Early detection of population changes prompts timely conservation actions.

Agricultural Benefits:

Supports pollination and natural pest control, crucial for crop yields and food security.
Aids in developing sustainable farming practices.

Biodiversity Conservation:

Helps protect endangered insect species by providing accurate population data.
Informs strategies for habitat preservation and restoration.