An Early Diagnosis of Oral Cancer based on Three-Dimensional Convolutional Neural Networks. - Shipu Xu; Yong Liu; Wenwen Hu; Chenxi Zhang 001; Chang Liu 037; Yongshuo Zong; Sirui Chen; Yiwen Lu; Longzhi Yang; Eddie Y. K. Ng; Yongtong Wang; Yunsheng Wang (IEEE Access, 2019)

A Deep Transfer Convolutional Neural Network Framework for EEG Signal Classification. - Gaowei Xu; Xiaoang Shen; Sirui Chen; Yongshuo Zong; Canyang Zhang; Hongyang Yue; Min Liu 002; Fei Chen; Wenliang Che (IEEE Access, 2019)

Automatic Detection Approach for Bioresorbable Vascular Scaffolds Using a U-Shaped Convolutional Neural Network. - Wen Zhou 005; Fei Chen; Yongshuo Zong; Dadong Zhao; Biao Jie; Zhengdong Wang; Chenxi Huang 001; Eddie-Yin-Kwee Ng (IEEE Access, 2019)

U-net Based Method for Automatic Hard Exudates Segmentation in Fundus Images Using Inception Module and Residual Connection. - Yongshuo Zong; Jinling Chen; Lvqing Yang; Siyi Tao; Cieryouzhen Aoma; Jiangsheng Zhao; Shuihua Wang (IEEE Access, 2020)

Magnetic Resonance Image Denoising Algorithm Based on Cartoon, Texture, and Residual Parts. - Yanqiu Zeng; Baocan Zhang; Wei Zhao 059; Shixiao Xiao; Guokai Zhang; Haiping Ren; Wenbing Zhao 001; Yonghong Peng; Yutian Xiao; Yiwen Lu; Yongshuo Zong; Yimin Ding (Comput. Math. Methods Medicine, 2020)

Moving Window Differential Evolution Independent Component Analysis-Based Operational Modal Analysis for Slow Linear Time-Varying Structures. - Yongshuo Zong; Jinling Chen; Siyi Tao; Cheng Wang 020; Jianbing Xiahou (Sci. Program., 2020)

A new deep learning approach for the retinal hard exudates detection based on superpixel multi-feature extraction and patch-based CNN. - Chenxi Huang 001; Yongshuo Zong; Yimin Ding; Xin Luo 001; Kathy Clawson; Yonghong Peng (Neurocomputing, 2021)

A Deep Segmentation Network of Stent Structs Based on IoT for Interventional Cardiovascular Diagnosis. - Chenxi Huang 001; Yongshuo Zong; Jinling Chen; Weipeng Liu; Jaime Lloret 001; Mithun Mukherjee 001 (IEEE Wirel. Commun., 2021)

Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn. - Ondrej Bohdal; Yinbing Tian; Yongshuo Zong; Ruchika Chavhan; Da Li 001; Henry Gouk; Li Guo; Timothy M. Hospedales (CVPR, 2023)

MEDFAIR: Benchmarking Fairness for Medical Imaging. - Yongshuo Zong; Yongxin Yang; Timothy M. Hospedales (ICLR, 2023)

What If the TV was off? Examining Counterfactual Reasoning Abilities of Multi-modal Language Models. - Letian Zhang; Xiaotong Zhai; Zhongkai Zhao; Yongshuo Zong; Xin Wen 004; Bingchen Zhao (CVPR, 2024)

Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models. - Yongshuo Zong; Ondrej Bohdal; Tingyang Yu; Yongxin Yang; Timothy M. Hospedales (ICML, 2024)

Fool Your (Vision and) Language Model with Embarrassingly Simple Permutations. - Yongshuo Zong; Tingyang Yu; Ruchika Chavhan; Bingchen Zhao; Timothy M. Hospedales (ICML, 2024)

VL-ICL Bench: The Devil in the Details of Benchmarking Multimodal In-Context Learning. - Yongshuo Zong; Ondrej Bohdal; Timothy M. Hospedales (CoRR, 2024)

Benchmarking Multi-Image Understanding in Vision and Language Models: Perception, Knowledge, Reasoning, and Multi-Hop Reasoning. - Bingchen Zhao; Yongshuo Zong; Letian Zhang; Timothy M. Hospedales (CoRR, 2024)

Memorized Images in Diffusion Models share a Subspace that can be Located and Deleted. - Ruchika Chavhan; Ondrej Bohdal; Yongshuo Zong; Da Li 001; Timothy M. Hospedales (CoRR, 2024)

A Preliminary Study of o1 in Medicine: Are We Closer to an AI Doctor? - Yunfei Xie; Juncheng Wu; Haoqin Tu; Siwei Yang; Bingchen Zhao; Yongshuo Zong; Qiao Jin; Cihang Xie; Yuyin Zhou (CoRR, 2024)

Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels. - Yongshuo Zong; Qin Zhang; Dongsheng An; Zhihua Li; Xiang Xu; Linghan Xu; Zhuowen Tu; Yifan Xing; Onkar Dabeer (CVPR, 2025)

VL-ICL Bench: The Devil in the Details of Multimodal In-Context Learning. - Yongshuo Zong; Ondrej Bohdal; Timothy M. Hospedales (ICLR, 2025)

Self-Supervised Multimodal Learning: A Survey. - Yongshuo Zong; Oisin Mac Aodha; Timothy M. Hospedales (IEEE Trans. Pattern Anal. Mach. Intell., 2025)