Search Results for author: Kun Gao

Found 7 papers, 0 papers with code

Probabilistic Prediction of Longitudinal Trajectory Considering Driving Heterogeneity with Interpretability

no code implementations19 Dec 2023 Shuli Wang, Kun Gao, Lanfang Zhang, Yang Liu, Lei Chen

Specifically, based on a certain length of historical trajectory data, the situation-specific driving preferences of each driver are identified, where key driving behavior feature vectors are extracted to characterize heterogeneity in driving behavior among different drivers.

Navigate Trajectory Prediction

Joint Sparse Representations and Coupled Dictionary Learning in Multi-Source Heterogeneous Image Pseudo-color Fusion

no code implementations15 Oct 2023 Long Bai, Shilong Yao, Kun Gao, Yanjun Huang, Ruijie Tang, Hong Yan, Max Q. -H. Meng, Hongliang Ren

Considering that Coupled Dictionary Learning (CDL) method can obtain a reasonable linear mathematical relationship between resource images, we propose a novel CDL-based Synthetic Aperture Radar (SAR) and multispectral pseudo-color fusion method.

Dictionary Learning

Reinforcement Logic Rule Learning for Temporal Point Processes

no code implementations11 Aug 2023 Chao Yang, Lu Wang, Kun Gao, Shuang Li

Leveraging the temporal point process modeling and learning framework, the rule content and weights will be gradually optimized until the likelihood of the observational event sequences is optimal.

Point Processes

Learning First-Order Rules with Differentiable Logic Program Semantics

no code implementations28 Apr 2022 Kun Gao, Katsumi Inoue, Yongzhi Cao, Hanpin Wang

We map the symbolic forward-chained format of LPs into NN constraint functions consisting of operations between subsymbolic vector representations of atoms.

Inductive logic programming

Merging Control Strategies of Connected and Autonomous Vehicles at Freeway On-Ramps: A Comprehensive Review

no code implementations18 Feb 2022 Jie Zhu, Said Easa, Kun Gao

This paper presents a comprehensive review of the existing ramp merging strategies leveraging CAVs, focusing on the latest trends and developments in the research field.

Autonomous Vehicles

Multi-Site Infant Brain Segmentation Algorithms: The iSeg-2019 Challenge

no code implementations4 Jul 2020 Yue Sun, Kun Gao, Zhengwang Wu, Zhihao Lei, Ying WEI, Jun Ma, Xiaoping Yang, Xue Feng, Li Zhao, Trung Le Phan, Jitae Shin, Tao Zhong, Yu Zhang, Lequan Yu, Caizi Li, Ramesh Basnet, M. Omair Ahmad, M. N. S. Swamy, Wenao Ma, Qi Dou, Toan Duc Bui, Camilo Bermudez Noguera, Bennett Landman, Ian H. Gotlib, Kathryn L. Humphreys, Sarah Shultz, Longchuan Li, Sijie Niu, Weili Lin, Valerie Jewells, Gang Li, Dinggang Shen, Li Wang

Deep learning-based methods have achieved state-of-the-art performance; however, one of major limitations is that the learning-based methods may suffer from the multi-site issue, that is, the models trained on a dataset from one site may not be applicable to the datasets acquired from other sites with different imaging protocols/scanners.

Brain Segmentation

An Effective Training Method For Deep Convolutional Neural Network

no code implementations31 Jul 2017 Yang Jiang, Zeyang Dou, Qun Hao, Jie Cao, Kun Gao, Xi Chen

In this paper, we propose the nonlinearity generation method to speed up and stabilize the training of deep convolutional neural networks.

Object Recognition

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