Situ Imageomics

Situ imageomics uses machine learning to extract biological or material properties directly from images captured in real-time during experiments or field observations. Current research focuses on improving data acquisition methods, such as optimizing autonomous drone flights for wildlife monitoring, and developing advanced image processing techniques, including U-Net and ResNet architectures, to enhance image quality and extract meaningful information from noisy or low-resolution data. This approach offers significant advantages in various fields, enabling more efficient process monitoring in manufacturing (e.g., 3D printing) and providing richer, more contextualized data for biological studies and conservation efforts.