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Real-time image semantic segmentation method and system, readable storage medium and terminal

A semantic segmentation and real-time image technology, applied in the field of image processing, to achieve the effect of enhancing information interaction and improving accuracy

Active Publication Date: 2019-08-02
NANJING UNIV OF POSTS & TELECOMM
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, those precise networks that require a lot of resources are not suitable for mobile platforms (e.g., drones, robots, and smartphones) with limited resources such as computing power, storage capacity, and energy overhead.

Method used

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  • Real-time image semantic segmentation method and system, readable storage medium and terminal
  • Real-time image semantic segmentation method and system, readable storage medium and terminal
  • Real-time image semantic segmentation method and system, readable storage medium and terminal

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Embodiment Construction

[0044] The following will clearly and completely describe the technical solutions in the embodiments of the application with reference to the drawings in the embodiments of the application. Apparently, the described embodiments are only some of the embodiments of the application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application. The relevant directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship between the components in a certain posture (as shown in the drawings). Sports conditions, etc., if the specific posture changes, the directional indication will also change accordingly.

[0045] As mentioned in the background, many lightweight networks in the prior art are designed to balance ...

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Abstract

The invention discloses a real-time image semantic segmentation method and system, a readable storage medium and a terminal. The method comprises the steps that an encoder carries out convolution operation on an input original feature image by utilizing a convolution unit based on feature channel splitting and rearrangement so as to extract image features and output the image features to a decoder; and the decoder adopts an attention pyramid network model to carry out intensive feature extraction on the output feature image of the encoder, maps the extracted feature to a segmentation category,and finally samples a segmentation result to an input original feature image resolution. According to the scheme, when the real-time image semantic segmentation is carried out by using limited computing resources, the segmentation accuracy is improved.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a real-time image semantic segmentation method and system, a readable storage medium and a terminal. Background technique [0002] Recently, building larger and deeper convolutional neural networks (CNNs, Convolutional Neural Networks) has become a major trend in solving scene understanding tasks. The most accurate CNNs typically have hundreds of convolutional layers and thousands of feature channels, and despite achieving higher performance, these advances come at the expense of model runtime and speed. Especially in the context of many real-world scenarios such as augmented reality, robotics, and self-driving cars, real-time prediction and evaluation of networks under resource-constrained conditions is often required. Therefore, those precise networks that require a lot of resources are not suitable for mobile platforms (e.g., drones, robots, and smartphon...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/24
Inventor 周全王雨从德春卢竞男刘嘉
Owner NANJING UNIV OF POSTS & TELECOMM
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