Research on intelligent recognition technology of visible light inspection images of power transmission drones based on faster RCNN

This article presents a novel Faster RCNN-based approach for detecting transmission line targets, aiming to overcome limitations of traditional methods. When it comes to feature extraction, it employs ResNet as its backbone, harnessing the prowess of its intricate convolutional layers and ingenious residual connections to capture intricate and diverse features. To accommodate targets of varying scales, the Feature Pyramid Network (FPN) is integrated, effectively blending shallow and deep features. Thorough experiments have demonstrated the model's efficacy, resulting in substantial gains in detection accuracy and recall, thereby providing fresh insights into intelligent recognition of visible light inspection images captured by power transmission drones.