Visual SLAM closed-loop detection method based on convolutional neural network and VLAD
A convolutional neural network and closed-loop detection technology, which is applied in the field of closed-loop detection based on convolutional neural network and VLAD, can solve problems such as lack of robustness
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment
[0045] The specific implementation process is as figure 1 Shown:
[0046] The first step is to construct a network model that integrates VGG16 and VLAD. figure 2 A schematic diagram of the constructed network model. The network is divided into two parts: the VGG16 partial structure and the NetVLAD pooling layer. The first part removes the pooling layer and the fully connected layer after the last convolutional layer conv5_3 of VGG16, including the RELU activation function. As the last layer of the network, NetVLAD can be decomposed into several basic CNN layers and connected to form a directed acyclic graph. The soft-assignment process can be divided into two steps: 1) The feature {x i} Through a convolution layer containing K 1×1 convolution kernels, the output is obtained: 2) then s k (x i ) is obtained by the soft-max function After obtaining the matrix V, it is necessary to perform L2 normalization on each column of D-dimensional vectors in V, convert the matrix ...
PUM
![No PUM](https://static-eureka.patsnap.com/ssr/23.2.0/_nuxt/noPUMSmall.5c5f49c7.png)
Abstract
Description
Claims
Application Information
![application no application](https://static-eureka.patsnap.com/ssr/23.2.0/_nuxt/application.06fe782c.png)
- 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.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap