Xin Liu

Orcid: 0000-0003-4083-4731

Affiliations:
  • Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, China


According to our database1, Xin Liu authored at least 12 papers between 2021 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2025
A Multi-scale Feature Fusion Network Focusing on Small Objects in UAV-View.
Cogn. Comput., April, 2025

BotVIO: A Lightweight Transformer-Based Visual-Inertial Odometry for Robotics.
IEEE Trans. Robotics, 2025

2024
Fine-MVO: Toward Fine-Grained Feature Enhancement for Self-Supervised Monocular Visual Odometry in Dynamic Environments.
IEEE Trans. Intell. Transp. Syst., October, 2024

Lite-SVO: Towards A Lightweight Self-Supervised Semantic Visual Odometry Exploiting Multi-Feature Sharing Architecture.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

2023
FastAdaBelief: Improving Convergence Rate for Belief-Based Adaptive Optimizers by Exploiting Strong Convexity.
IEEE Trans. Neural Networks Learn. Syst., September, 2023

Randomized block-coordinate adaptive algorithms for nonconvex optimization problems.
Eng. Appl. Artif. Intell., May, 2023

Towards Faster Training Algorithms Exploiting Bandit Sampling From Convex to Strongly Convex Conditions.
IEEE Trans. Emerg. Top. Comput. Intell., April, 2023

GSL-VO: A Geometric-Semantic Information Enhanced Lightweight Visual Odometry in Dynamic Environments.
IEEE Trans. Instrum. Meas., 2023

2022
LightAdam: Towards a Fast and Accurate Adaptive Momentum Online Algorithm.
Cogn. Comput., 2022

2021
FastAdaBelief: Improving Convergence Rate for Belief-based Adaptive Optimizer by Strong Convexity.
CoRR, 2021

DAda-NC: A Decoupled Adaptive Online Training Algorithm for Deep Learning Under Non-convex Conditions.
Proceedings of the Cognitive Systems and Information Processing, 2021

A Scalable 3D Array Architecture for Accelerating Convolutional Neural Networks.
Proceedings of the Cognitive Systems and Information Processing, 2021


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