It's hard to point to one specific architecture suitable for adding applications. Our customers have many different use cases for image annotation, such as identifying people in traffic cameras, cancerous cells in microscope slates, safety equipment in factory lines, and many more. A widely adopted and highly effective architecture for object detection is the Faster R-CNN (Region-based Convolutional Neural Network). It offers a good balance between accuracy and speed, making it suitable for many object detection tasks. It has been widely adopted and has achieved state-of-the-art performance on benchmarks and computer vision models like COCO (Common Objects in Context).