Sdnia Yolo

SDNIA-YOLO represents a family of object detection models based on the YOLO architecture, primarily focused on improving robustness and accuracy in challenging conditions. Current research emphasizes adapting YOLO for specific applications, such as wildlife detection from UAV imagery, PCB defect identification, and navigation using fiducial markers, often incorporating novel modules to enhance feature extraction and handling of small or occluded objects. These advancements are significant for various fields, including automated inspection, robotics, and autonomous systems, by enabling more reliable and efficient object detection in real-world scenarios with complex visual data.