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Deep semantic segmentation-based ocean oil spill detection system and method

A semantic segmentation and detection method technology, applied in the direction of instruments, biological neural network models, character and pattern recognition, etc., can solve problems such as damage to the marine environment and difficulties in monitoring work

Inactive Publication Date: 2018-09-28
SHENZHEN POLYTECHNIC
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Problems solved by technology

This has also brought a heavy burden to the marine ecological environment, especially the marine oil spill pollution has caused huge damage to the marine environment, and also suffered huge economic losses.
Marine oil spills often occur under severe weather conditions, which makes monitoring work difficult

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  • Deep semantic segmentation-based ocean oil spill detection system and method

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Embodiment Construction

[0019] The present invention will be further described below in conjunction with the description of the drawings and specific embodiments.

[0020] The present invention provides a marine oil spill detection system based on deep semantic segmentation, which includes a computing server, a GPU cluster, a marine pollution remote sensing image database, and a normal pollution-free image database. The computing server is deployed on the GPU cluster, and the computing server stores The trained neural network model is used to recognize the input image.

[0021] like figure 1 As shown, the present invention also provides a method for detecting marine oil spills based on depth semantic segmentation, comprising the following steps:

[0022] S1. Data set preparation;

[0023] S2, data preprocessing;

[0024] S3, network structure design;

[0025] 1. Vgg+FCN semantic segmentation network;

[0026] 2. Googlenet + Fcn;

[0027] 3. Resnet + FCN;

[0028] 4. U-net;

[0029] S4. Neural...

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Abstract

The invention provides a deep semantic segmentation-based ocean oil spill detection system. The system comprises a computing server, a GPU cluster, an ocean pollution remote sensing image database anda normal no-pollution image database; the computing server is deployed on the GPU cluster; the computing server stores a trained neural network model; and an input image is identified. The inventionfurthermore provides a deep semantic segmentation-based ocean oil spill detection method. The system and the method have the beneficial effects that the ocean oil spill pollution can be quickly and accurately monitored.

Description

technical field [0001] The invention relates to oil spill detection, in particular to a method for detecting marine oil spills based on depth semantic segmentation. Background technique [0002] The 21st century is a new period for large-scale development and utilization of marine resources, expansion of marine industry and development of marine economy in the world. This has also brought a heavy burden to the marine ecological environment, especially the marine oil spill pollution has caused huge damage to the marine environment, and also suffered huge economic losses. Marine oil spills often occur under severe weather conditions, which brings many difficulties to the monitoring work. With the development of satellite remote sensing technology, the performance of various remote sensing platforms and sensors has been continuously improved, making it possible to quickly and accurately monitor marine oil spill pollution. At the same time, the rise of deep learning has furthe...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04
CPCG06V20/46G06N3/045G06F18/241
Inventor 李岩杨小飞
Owner SHENZHEN POLYTECHNIC
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