49 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
7 papers
Look Clearly Before Answering: Mitigating Hallucinations in LVLMs via Saliency-Driven Perceptual Realignment
Pengxu Chen, Yao Zhu, Guangming Zhu +4
Large vision-language models (LVLMs) have demonstrated remarkable capabilities in multimodal understanding. However, they remain prone to hallucinations, generating responses that…
3MOS: Multi-sources, Multi-resolutions, and Multi-scenes dataset for Optical-SAR image matching
Yibin Ye, Xichao Teng, Shuo Chen +3
Optical-SAR image matching is a fundamental task for image fusion and visual navigation. However, all large-scale open SAR dataset for methods development are collected from single…
Oriented object detection in optical remote sensing images using deep learning: a survey
Kun Wang, Zi Wang, Zhang Li +5
Oriented object detection is a fundamental yet challenging task in remote sensing (RS), aiming to locate and classify objects with arbitrary orientations. Recent advancements in de…
Bayesian inference using intermediate distribution based on coarse multiscale model for time fractional diffusion equation
Lijian Jiang, Na Ou
In the paper, we present a strategy for accelerating posterior inference for unknown inputs in time fractional diffusion models. In many inference problems, the posterior may be co…
Incompressible Limit of isentropic Navier-Stokes equations with Navier-slip boundary
Xiong Linjie
This paper concerns the low Mach number limit of weak solutions to the compressible Navier-Stokes equations for isentropic fluids in a bounded domain with a Navier-slip boundary co…
A novel variable-separation method based on sparse representation for stochastic partial differential equations
Qiuqi Li, Lijian Jiang
In this paper, we propose a novel variable-separation (NVS) method for generic multivariate functions. The idea of NVS is extended to to obtain the solution in tensor product struc…
Multiscale model reduction method for Bayesian inverse problems of subsurface flow
Lijian Jiang, Na Ou
This work presents a model reduction approach to the inverse problem in the application of subsurface flows. For the Bayesian inverse problem, the forward model needs to be repeate…