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Object Localization Algorithm Based on Meta-Reinforcement Learning Cover

Object Localization Algorithm Based on Meta-Reinforcement Learning

International Journal of Advanced Network, Monitoring and Controls
Volume 8 (2023): Issue 4 (December 2023)
By: Han Yan and  Hong Jiang  
Open Access
|Mar 2024

Figures & Tables

Figure 1.

Process of target localization in meta-reinforcement learning
Process of target localization in meta-reinforcement learning

Figure 2.

Object localization model
Object localization model

Figure 3.

Action diagram
Action diagram

Figure 4.

Structure of the location network
Structure of the location network

Figure 5.

Structure of the regression network
Structure of the regression network

Figure 6.

Feature network structure
Feature network structure

Figure 7.

Training process of meta-parameter pooling
Training process of meta-parameter pooling

Figure 8.

Parameter training process of meta-reinforcement learning
Parameter training process of meta-reinforcement learning

Figure 9.

Comparison of training loss functions
Comparison of training loss functions

Figure 10.

Results of ta
Results of ta

Figure 11.

Comparison of precision and recall
Comparison of precision and recall
DOI: https://doi.org/10.2478/ijanmc-2023-0077 | Journal eISSN: 2470-8038
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Language: English
Page range: 55 - 65
Published on: Mar 16, 2024
Published by: Xi’an Technological University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Meta-reinforcement Learning,
Meta-Parameter,
Target,
Generalization Ability,
Deep Reinforcement Learning
Related subjects:
Computer sciences,
Computer sciences, other

© 2024 Han Yan, Hong Jiang, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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