Xintong Shi

According to our database, Xintong Shi authored at least 9 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Bipartite Graph Approximation by Eigenvalue Optimization.

Aimin Jiang, Xintong Shi, Yibin Tang, Yanping Zhu, Hon Keung Kwan

IEEE Trans. Signal Inf. Process. over Networks, 2024

mmGAT: Pose Estimation by Graph Attention with Mutual Features from mmWave Radar Point Cloud.

Abdullah Al Masud, Xintong Shi, Mondher Bouazizi, Tomoaki Ohtsuki

Proceedings of the IEEE International Conference on Communications, 2024

2023

A Robust Approach Assisted by Signal Quality Assessment for Fetal Heart Rate Estimation from Doppler Ultrasound Signal.

Xintong Shi, Natsuho Niida, Kohei Yamamoto, Tomoaki Ohtsuki, Yutaka Matsui, Kazunari Owada

Sensors, December, 2023

Deep neural networks for rank-consistent ordinal regression based on conditional probabilities.

Xintong Shi, Wenzhi Cao, Sebastian Raschka

Pattern Anal. Appl., August, 2023

A Robust Multi-Frame mmWave Radar Point Cloud-Based Human Skeleton Estimation Approach with Point Cloud Reliability Assessment.

Xintong Shi, Tomoaki Ohtsuki

Proceedings of the 2023 IEEE SENSORS, Vienna, Austria, October 29 - Nov. 1, 2023, 2023

A Rank Constrained Approach for Graph Learning from Spatio-Temporal Signals.

Ziqian Yue, Aimin Jiang, Xintong Shi

Proceedings of the 16th International Congress on Image and Signal Processing, 2023

2022

Unsupervised Representation Learning-based Doppler Ultrasound Signal Quality Assessment.

Xintong Shi, Kohei Yamamoto, Tomoaki Ohtsuki, Yutaka Matsui, Kazunari Owada

Proceedings of the IEEE Global Communications Conference, 2022

Non-invasive Fetal ECG Signal Quality Assessment based on Unsupervised Learning Approach.

Xintong Shi, Kohei Yamamoto, Tomoaki Ohtsuki, Yutaka Matsui, Kazunari Owada

Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

2020

Customized Inverse Design of Metamaterial Absorber Based on Target-Driven Deep Learning Method.

Junjie Hou, Hai Lin, Weilin Xu, Yuze Tian, You Wang, Xintong Shi, Feng Deng, Lijie Chen

IEEE Access, 2020