Real Time Object

Real-time object detection focuses on rapidly and accurately identifying objects within visual data, crucial for applications demanding immediate responses like autonomous driving and robotics. Current research emphasizes improving the speed and accuracy of detection using various architectures, including YOLO (You Only Look Once) and Transformer-based models, often incorporating techniques like quantization and efficient convolution operations to optimize performance on resource-constrained devices. This field significantly impacts numerous sectors by enabling safer and more efficient systems, ranging from advanced driver-assistance systems to industrial automation and assistive technologies for the visually impaired.