SSD-based target detection improved algorithm

A technology of target detection and improved algorithm, which is applied in computing, computer components, instruments, etc., can solve problems such as target detection accuracy needs to be improved, network model performance is not good, and SSD network parameters have a large amount of calculation, so as to improve performance and The effect of detecting accuracy, reducing memory resource consumption, and reducing calculation load

Pending Publication Date: 2020-03-31
TIANJIN UNIV
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Problems solved by technology

The detection performance of SSD is relatively better, but there are still many shortcomings: the calculation of SSD network parameters is relatively large, the performance of the network model is not good, and the detection accuracy of target detection needs to be improved

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  • SSD-based target detection improved algorithm
  • SSD-based target detection improved algorithm
  • SSD-based target detection improved algorithm

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Embodiment Construction

[0037] The present invention will be further described below in conjunction with the accompanying drawings.

[0038] Such as figure 1 As shown, it is a schematic flowchart of an improved algorithm of SSD-based target detection provided by the present invention. Specifically include the following steps:

[0039] Step (1), image is input;

[0040] Step (2), the image input in step (1) is preprocessed, which can enrich the image training set and better extract image features;

[0041] Step (3), sending the preprocessed image into the deep residual network ResNet for a series of convolution processing;

[0042] Step (4), utilize deep residual network ResNet to carry out feature extraction, extract key information such as background, object, contour, color difference of input picture;

[0043] Step (5), the features extracted in step 4 are sent to the SSD network for re-extraction, and positioning and classification of pictures;

[0044] Step (6), finally output the target de...

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Abstract

The invention discloses an SSD-based target detection improved algorithm. The SSD-based target detection improved algorithm comprises the steps of 1, inputting an image; 2, preprocessing the image input in the step 1; 3, sending the preprocessed image into a deep residual error network (ResNet) to carry out a series of convolution processing; 4, performing feature extraction by using a convolutional network, and extracting key information of the input picture; 5, sending the features extracted in the step 4 into an SSD network for re-extraction, and positioning and classifying the pictures; and 6, finally outputting a target detection result of the image. Compared with the prior art, the algorithm can be well used for target detection, the calculation amount is reduced, hardware memory resource consumption is reduced, the network model performance and the detection accuracy are improved, the detection accuracy is improved by 3.6% compared with a classic SSD algorithm, and good robustness is achieved. The method has important significance and reference value for further application of the deep learning technology to target detection.

Description

technical field [0001] The invention relates to the field of target detection, in particular to an improved algorithm for target detection based on SSD. Background technique [0002] Object detection has become an important research direction and research hotspot in the field of computer vision, and can be applied to unmanned driving, robots, video surveillance, pedestrian detection, sea ship detection and other fields. Before the emergence of deep learning, the target detection method was mainly completed by establishing a certain mathematical model based on certain prior knowledge. The widely used methods are: Hough transform, frame difference method, background subtraction method, optical flow method, sliding method, etc. Window models, deformable part models, etc. In recent years, the emergence of deep learning technology has revolutionized the mode of target detection and improved the accuracy and robustness of target detection. [0003] Currently, object detection me...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06V2201/07G06F18/2413G06F18/29
Inventor 苏寒松乔婷刘高华
Owner TIANJIN UNIV
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