1 citations · 2 across the 6 of their papers we have counts for
6 papers
Taming a Retrieval Framework to Read Images in Humanlike Manner for Augmenting Generation of MLLMs
Suyang Xi, Chenxi Yang, Hong Ding +4
Multimodal large language models (MLLMs) often fail in fine-grained visual question answering, producing hallucinations about object identities, positions, and relations because te…
Copula-enhanced Vision Transformer for high myopia diagnosis through OU UWF fundus images
Chong Zhong, Yunhao Liu, Yang Li +10
The advancement of AI-assisted myopia screening necessitates the joint diagnosis of both-eye (OU) high myopia (HM) status and the prediction of axial length (AL). This clinical req…
On MCMC mixing for predictive inference under unidentified transformation models
Chong Zhong, Jin Yang, Junshan Shen +2
Reliable Bayesian predictive inference has long been an open problem under unidentified transformation models, since the Markov Chain Monte Carlo (MCMC) chains of posterior predict…
OU-CoViT: Copula-Enhanced Bi-Channel Multi-Task Vision Transformers with Dual Adaptation for OU-UWF Images
Yang Li, Jianing Deng, Chong Zhong +7
Myopia screening using cutting-edge ultra-widefield (UWF) fundus imaging and joint modeling of multiple discrete and continuous clinical scores presents a promising new paradigm fo…
OUCopula: Bi-Channel Multi-Label Copula-Enhanced Adapter-Based CNN for Myopia Screening Based on OU-UWF Images
Yang Li, Qiuyi Huang, Chong Zhong +7
Myopia screening using cutting-edge ultra-widefield (UWF) fundus imaging is potentially significant for ophthalmic outcomes. Current multidisciplinary research between ophthalmolog…
CeCNN: Copula-enhanced convolutional neural networks in joint prediction of refraction error and axial length based on ultra-widefield fundus images
Chong Zhong, Yang Li, Danjuan Yang +5
The ultra-widefield (UWF) fundus image is an attractive 3D biomarker in AI-aided myopia screening because it provides much richer myopia-related information. Though axial length (A…