Multimodal sensory fusion for soccer robot self-localization based on long short-term memory recurrent neural network

By Wenhuan Lu, Ju Zhang, Xinlin Zhao, Jianrong Wang, Jianwu Dang. 2017

18 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Ala Al-Fuqaha
2. Mohsen Guizani

In Computer Vision and Pattern Recognition

1. Ala Al-Fuqaha
2. Mohsen Guizani
3. Sameh Sorour
4. M. Mohammadi
5. Umair Mohammad

In Electrical and Electronic Engineering

1. Ala Al-Fuqaha
2. M. Mohammadi
3. Mohsen Guizani
4. Sameh Sorour

Citations in the corpus

• Deep Learning for IoT Big Data and Streaming Analytics: A Survey (2017, methodology): “over, a CNN has been trained in [96] to determine the indoor positions of users by analyzing an image from their surrounding scene. Lu et al. have also used LSTM networks for localizing soccer robots [97]. In this application, data collected from several sensors, namely Inertia Navigation System (IN”