Object Detection With Text Based Coordinate Output

via “object detection and localization with coordinate output”

Tiny vision-language model for edge devices.

Unique: Region encoder subsystem maps visual features directly to coordinate embeddings without separate detection head; uses coordinate transformations to convert pixel-space outputs to normalized or absolute coordinates, enabling end-to-end detection without post-processing bounding box regression layers.

vs others: Integrated into single model (no separate detection pipeline) and runs on edge devices; slower than optimized YOLO but requires no additional model loading or inference overhead.