Abstract: A ship detection method and system based on multidimensional scene features, wherein the method includes: constructing a ship image sample database, and extracting all the edges of each frame of image to act as a fourth dimension of the image; extracting a coastline to make a sea surface area be a ship area; constructing a Faster RCNN-like convolutional network to act as a deep learning network, and inputting sample data into the deep learning network; constructing an RPN network, using a sliding window to generate region proposal boxes of different sizes in the ship area, combining the region proposal boxes with the deep learning network, and training a model according to an actual position of a ship; and performing ship detection on a part of the detected image between the coastline on the basis of the trained model.

Abstract: An automatic ship tracking method and system based on deep learning network and mean shift, wherein the method includes: collecting surveillance video data which includes collecting coastal region surveillance video data under visible light and extracting each frame of image; performing preprocessing to extract a positive sample and a negative sample of a ship target; inputting the samples of the ship target in the video into a neural network to train a model by a region-based convolutional neural network method; extracting initial frame data of the video and performing ship detection and probability density calculation on initial moment data according to the trained model; and determining a ship tracking result at the current moment by a calculation result of a previous moment.

Abstract: A ship detection method and system based on multidimensional scene features, wherein the method includes: constructing a ship image sample database, and extracting all the edges of each frame of image to act as a fourth dimension of the image; extracting a coastline to make a sea surface area be a ship area; constructing a Faster RCNN-like convolutional network to act as a deep learning network, and inputting sample data into the deep learning network; constructing an RPN network, using a sliding window to generate region proposal boxes of different sizes in the ship area, combining the region proposal boxes with the deep learning network, and training a model according to an actual position of a ship; and performing ship detection on a part of the detected image between the coastline on the basis of the trained model.

Abstract: An automatic ship tracking method and system based on deep learning network and mean shift, wherein the method includes: collecting surveillance video data which includes collecting coastal region surveillance video data under visible light and extracting each frame of image; performing preprocessing to extract a positive sample and a negative sample of a ship target; inputting the samples of the ship target in the video into a neural network to train a model by a region-based convolutional neural network method; extracting initial frame data of the video and performing ship detection and probability density calculation on initial moment data according to the trained model; and determining a ship tracking result at the current moment by a calculation result of a previous moment.