Road scene semantic segmentation method based on convolutional neural network
A convolutional neural network and semantic segmentation technology, applied in the field of semantic segmentation of deep learning, can solve the problems of image feature information reduction, low segmentation accuracy, and non-representative
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment Construction
[0042] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.
[0043] A method for road scene semantic segmentation based on convolutional neural network proposed by the present invention, its overall realization block diagram is as follows figure 1 As shown, it includes two processes of training phase and testing phase;
[0044] Described step 1_1 is specifically:
[0045] Select Q original road scene images and the real semantic segmentation images corresponding to each original road scene image, and select the qth original road scene image as The heat map corresponding to the original road scene image is denoted as Using the HHA coding method to process the thermal image into three channels and superimpose it with the original road scene image to form a color thermal image, which is recorded as Record the real semantic segmentation image corresponding to the qth original road scene image as
...
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com