Yongshuo Zong

Orcid: 0000-0002-3267-753X

According to our database1, Yongshuo Zong authored at least 15 papers between 2019 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
VL-ICL Bench: The Devil in the Details of Benchmarking Multimodal In-Context Learning.
CoRR, 2024

Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models.
CoRR, 2024

2023
What If the TV Was Off? Examining Counterfactual Reasoning Abilities of Multi-modal Language Models.
CoRR, 2023

Fool Your (Vision and) Language Model With Embarrassingly Simple Permutations.
CoRR, 2023

Self-Supervised Multimodal Learning: A Survey.
CoRR, 2023

MEDFAIR: Benchmarking Fairness for Medical Imaging.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2021
A Deep Segmentation Network of Stent Structs Based on IoT for Interventional Cardiovascular Diagnosis.
IEEE Wirel. Commun., 2021

A new deep learning approach for the retinal hard exudates detection based on superpixel multi-feature extraction and patch-based CNN.
Neurocomputing, 2021

2020
Moving Window Differential Evolution Independent Component Analysis-Based Operational Modal Analysis for Slow Linear Time-Varying Structures.
Sci. Program., 2020

Magnetic Resonance Image Denoising Algorithm Based on Cartoon, Texture, and Residual Parts.
Comput. Math. Methods Medicine, 2020

U-net Based Method for Automatic Hard Exudates Segmentation in Fundus Images Using Inception Module and Residual Connection.
IEEE Access, 2020

2019
Automatic Detection Approach for Bioresorbable Vascular Scaffolds Using a U-Shaped Convolutional Neural Network.
IEEE Access, 2019

A Deep Transfer Convolutional Neural Network Framework for EEG Signal Classification.
IEEE Access, 2019

An Early Diagnosis of Oral Cancer based on Three-Dimensional Convolutional Neural Networks.
IEEE Access, 2019


  Loading...