CNN Based Detector

Convolutional neural network (CNN)-based detectors are a cornerstone of object detection in computer vision, aiming to accurately and efficiently locate and classify objects within images or videos. Current research emphasizes improving speed and accuracy, particularly in challenging scenarios like dense or rotated objects, indoor environments, and degraded imagery, often through hybrid approaches combining CNNs with transformer architectures or incorporating novel training strategies like knowledge distillation and label assignment modifications. These advancements have significant implications for diverse applications, including autonomous driving, augmented reality, and forensic image analysis, by enabling faster, more robust, and accurate object detection in real-world settings.