Video recognition method and system for shipping cargo monitoring based on convolutional neural network
A convolutional neural network and monitoring video technology, applied in the field of shipping cargo monitoring video recognition, can solve the problem of low recognition accuracy of shipping cargo monitoring video, and achieve the effect of ensuring the accuracy of classification
Active Publication Date: 2021-11-02
武汉恒视途安科技有限公司
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[0004] The purpose of the present invention is to provide a method and system for video recognition of shipping cargo monitoring based on convolutional neural network to solve the problem of low accuracy in video recognition of shipping cargo monitoring
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[0056] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0057] The purpose of the present invention is to provide a method and system based on a convolutional neural network for monitoring video of shipping cargo, which can improve the recognition accuracy of determining current shipping events through monitoring video of shipping cargo.
[0058] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in...
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The invention discloses a method and system for monitoring video recognition of shipping goods based on a convolutional neural network. The method includes: acquiring shipping monitoring data; establishing an image database according to the shipping monitoring data; generating a training set and a test set according to a proportional threshold according to the image database; establishing a deep residual network model according to the training set and the testing set ; extract the image features of each image in the image database according to the deep residual network model, and establish an image feature database; the image feature database includes image features and image feature vectors; establish according to the image feature database A neural network classifier; classify and identify the current shipping event according to the neural network classifier, and determine the shipping event category of the current shipping event. The identification method and system provided by the invention can improve the identification accuracy of the current shipping event.
Description
technical field [0001] The invention relates to the field of surveillance video recognition of shipping cargo, in particular to a method and system for video surveillance of shipping cargo based on a convolutional neural network. Background technique [0002] Due to the complexity and possible risks of various situations in the shipping process, the monitoring of the shipping process has always been an issue that the industry attaches great importance to. With the update of modern technology, the increasing development of the shipping industry and the increase in the number of ships, the previously widely used manual supervision method has been unable to meet the needs of the shipping process due to reasons such as high cost, large manpower consumption, and untimely feedback. monitoring needs. In this context, the use of more efficient machine supervision to replace manual supervision is the development trend of future shipping monitoring, and how to accurately judge the ty...
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IPC IPC(8): G06K9/00G06K9/62G06N3/04
CPCG06V20/41G06N3/045G06F18/24G06F18/214
Inventor 张鸿刘巍代刚赵亮
Owner 武汉恒视途安科技有限公司