Abstract
Ship target detection has urgent needs and broad application prospects in military and marine transportation. In order to improve the accuracy and efficiency of the ship target detection, an improved Faster R-CNN (Faster Region-based Convolutional Neural Network) algorithm of ship target detection is proposed. In the proposed method, the image downscaling method is used to enhance the useful information of the ship image. The scene narrowing technique is used to construct the target regional positioning network and the Faster R-CNN convolutional neural network into a hierarchical narrowing network, aiming at reducing the target detection search scale and improving the computational speed of Faster R-CNN. Furthermore, deep cooperation between main network and subnet is realized to optimize network parameters after researching Faster R-CNN with subject narrowing function and selecting texture features and spatial difference features as narrowed sub-networks. The experimental results show that the proposed method can significantly shorten the detection time of the algorithm while improving the detection accuracy of Faster R-CNN algorithm.
Highlights
With the development of social economy, inland navigation and ocean shipping are developing rapidly
The R-CNN proposed by Girshick [14] has made breakthroughs in the field of target detection, and successively appeared algorithms such as Spatial Pyramid Pooling (SPP), Fast Region-based Convolutional Neural Network (Fast R-CNN), Faster R-CNN, You Only
When the background is removed from the original image, the Faster R-CNN convolutional neural network detects and classifies the target from the ship target area
Summary
With the development of social economy, inland navigation and ocean shipping are developing rapidly. Krizhevsky et al [12] constructed a deep convolutional neural network in 2012 and achieved great success in large-scale image classification. The R-CNN proposed by Girshick [14] has made breakthroughs in the field of target detection, and successively appeared algorithms such as Spatial Pyramid Pooling (SPP), Fast Region-based Convolutional Neural Network (Fast R-CNN), Faster R-CNN, You Only. The innovative algorithm of deep learning is applied to the detection of ship targets, and the detection effect is significantly improved. The deep learning frameworks can learn the training image through the convolutional neural network and automatically extracts target features from the image. These frameworks have high learning ability, fast recognition speed and high detection precision. Proposed to improve the detection accuracy of Faster R-CNN algorithm and shorten the detection time of the algorithm
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
