Real-time object detection is one of the most challenging problems in computer vision. Recent advances in this field have significantly improved the accuracy and speed of object detection algorithms. However, there are still many challenges to be addressed, particularly when it comes to object detection in complex and cluttered scenes.
Improvements in hardware and computational power have played a crucial role in advancing the field of object detection. The availability of high-performance GPUs and specialized processors, along with the development of deep learning frameworks, has made it easier to train and deploy object detection models. These advancements have contributed to the improvement in object detection accuracy and speed.
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