A Novel Mobile Robot Localization Method Based on Global Vision System
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-6203-5_45
Reference8 articles.
1. Hu, B., Yu, Q., Yu, H.: Global Vision Localization of Indoor Service Robot Based on Improved Iterative Extended Kalman Particle Filter Algorithm. Journal of Sensors (2021). https://doi.org/10.1155/2021/8819917
2. Sun, X., Zhang, Y., Wang, H., et al.: Research on ship detection of optical remote sensing image based on Yolo V5. Journal of Physics: Conference Series. IOP Publishing. 2215(1), 012027 (2022). https://doi.org/10.1088/1742-6596/2215/1/012027
3. Zhang, X., Qian, B., Si, H., et al.: Research on the computer intelligent recognition of electric appliance by Yolo V5 algorithm. Journal of Physics: Conference Series. IOP Publishing. 2083(3), 032078 (2021). https://doi.org/10.1088/1742-6596/2083/3/032078
4. Kim, J., Kim, N., Park, Y., et al.: Object Detection and Classification Based on YOLO-V5 with Improved Maritime Dataset. Journal of Marine Science and Engineering. 10(3), 377 (2022). https://doi.org/10.3390/jmse10030377
5. Wu, W., Liu, H., Li, L., et al.: Application of local fully Convolutional Neural Network combined with YOLO v5 algorithm in small target detection of remote sensing image. PloS one. 16(10), e0259283 (2021). https://doi.org/10.1371/journal.pone.0259283
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