Marine ship target identification method
A target recognition and ship technology, applied in the field of target recognition, can solve the problems of inability to detect ships, low confidence, and low recognition accuracy, and achieve the effect of improving accuracy and recognition confidence
Active Publication Date: 2020-04-17
ANHUI UNIVERSITY OF TECHNOLOGY AND SCIENCE
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However, the traditional target detection algorithm can only extract edges and contours, but cannot complete target classification, so it cannot be applied to ship detection
Using SSD (Single shotmultibox detector) to extract deep feature informa
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[0021] The specific implementation of the present invention will be described in further detail below by describing the embodiments with reference to the accompanying drawings, so as to help those skilled in the art have a more complete, accurate and in-depth understanding of the inventive concepts and technical solutions of the present invention.
[0022] figure 1 It is a flowchart of a method for identifying a ship at sea according to an embodiment of the present invention. The method specifically includes the following steps:
[0023] S1, constructing a sample set of the ship target, the sample set includes a training sample set and a test sample set;
[0024] In the embodiment of the present invention, ship images containing ship objects are collected, and the types and positions of ship objects and backgrounds in the ship images are marked to form training samples and put into the training sample set. The training sample set includes a large number of marked objects. The...
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The invention discloses a marine ship target recognition method, and the method specifically comprises the following steps: S1, constructing a sample set of a ship target, wherein the sample set comprises a training sample set and a test sample set; s2, training a ship data training set based on the improved SSD network model, and obtaining a ship target recognition model, wherein the improved SSDnetwork model refers to adding an L2 regularization penalty term to a seventh layer of a neural network to reduce the feature sensitivity of the seventh layer; s3, testing the ship target recognitionmodel based on the ship test data set, outputting the ship target recognition model when the accuracy of ship target recognition is greater than an accuracy threshold, and executing the step S2 if the accuracy of ship target recognition is less than or equal to the accuracy threshold. The regularization is added to the seventh layer of the SSD network model, so that the value of the weight matrixof the seventh layer is reduced, the obstacle feature of the seventh layer is reduced, and the ship target recognition accuracy and recognition confidence are improved.
Description
technical field [0001] The invention belongs to the field of target identification, and relates to a method for identifying a target of a ship at sea. Background technique [0002] When unmanned boats sail at sea, it is inevitable to encounter some obstacles, such as ships that are sailing and ships operating at sea. For the safety of unmanned boats sailing at sea, it is also essential to detect obstacles at sea. [0003] In the existing research, common traditional target detection algorithms include: Sobel operator, Isotropic Sobel operator, Roberts operator and Prewitt operator, etc. However, the traditional target detection algorithm can only extract edges and contours, but cannot complete target classification, so it cannot be applied to ship detection. Using SSD (Single shotmultibox detector) to extract deep feature information of images to realize the recognition of specific content of objects has made a lot of progress in the field of unmanned driving, but for ship...
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Login to View More IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/13G06F18/24G06F18/214
Inventor 葛愿叶刚韩超黄宜庆刘硕胡俊祥
Owner ANHUI UNIVERSITY OF TECHNOLOGY AND SCIENCE