Search Results for author: Yukun Zhou

Found 24 papers, 14 papers with code

Improving Knowledge Distillation via Category Structure

1 code implementation ECCV 2020 Zailiang Chen, Xianxian Zheng, Hailan Shen, Ziyang Zeng, Yukun Zhou, Rongchang Zhao

Intra-category structure penalizes the structured relations in samples from the same category and inter-category structure focuses on cross-category relations at a category level.

Knowledge Distillation

Top Ten Challenges Towards Agentic Neural Graph Databases

no code implementations24 Jan 2025 Jiaxin Bai, ZiHao Wang, Yukun Zhou, Hang Yin, Weizhi Fei, Qi Hu, Zheye Deng, Jiayang Cheng, Tianshi Zheng, Hong Ting Tsang, Yisen Gao, Zhongwei Xie, Yufei Li, Lixin Fan, Binhang Yuan, Wei Wang, Lei Chen, Xiaofang Zhou, Yangqiu Song

This paper introduces Agentic Neural Graph Databases (Agentic NGDBs), which extend NGDBs with three core functionalities: autonomous query construction, neural query execution, and continuous learning.

Management

Enhancing Contrastive Learning for Retinal Imaging via Adjusted Augmentation Scales

no code implementations5 Jan 2025 Zijie Cheng, Boxuan Li, André Altmann, Pearse A Keane, Yukun Zhou

In this paper, we investigate the reasons for this suboptimal performance and hypothesize that the dense distribution of medical images poses challenges to the pretext tasks in contrastive learning, particularly in constructing positive and negative pairs.

Contrastive Learning Self-Supervised Learning

Open-Sora: Democratizing Efficient Video Production for All

1 code implementation29 Dec 2024 Zangwei Zheng, Xiangyu Peng, Tianji Yang, Chenhui Shen, Shenggui Li, Hongxin Liu, Yukun Zhou, Tianyi Li, Yang You

To facilitate the development and accessibility of artificial visual intelligence, we created Open-Sora, an open-source video generation model designed to produce high-fidelity video content.

Image to Video Generation Text-to-Image Generation +1

Model-GLUE: Democratized LLM Scaling for A Large Model Zoo in the Wild

1 code implementation7 Oct 2024 Xinyu Zhao, Guoheng Sun, Ruisi Cai, Yukun Zhou, Pingzhi Li, Peihao Wang, Bowen Tan, Yexiao He, Li Chen, Yi Liang, Beidi Chen, Binhang Yuan, Hongyi Wang, Ang Li, Zhangyang Wang, Tianlong Chen

As Large Language Models (LLMs) excel across tasks and specialized domains, scaling LLMs based on existing models has garnered significant attention, which faces the challenge of decreasing performance when combining disparate models.

Benchmarking model

MONICA: Benchmarking on Long-tailed Medical Image Classification

1 code implementation2 Oct 2024 Lie Ju, Siyuan Yan, Yukun Zhou, Yang Nan, Xiaodan Xing, Peibo Duan, ZongYuan Ge

We hope this codebase serves as a comprehensive and reproducible benchmark, encouraging further advancements in long-tailed medical image learning.

Benchmarking Image Classification +2

Dataset Growth

1 code implementation28 May 2024 Ziheng Qin, Zhaopan Xu, Yukun Zhou, Zangwei Zheng, Zebang Cheng, Hao Tang, Lei Shang, Baigui Sun, Xiaojiang Peng, Radu Timofte, Hongxun Yao, Kai Wang, Yang You

To tackle this challenge, we propose InfoGrowth, an efficient online algorithm for data cleaning and selection, resulting in a growing dataset that keeps up to date with awareness of cleanliness and diversity.

Diversity

OpenMEDLab: An Open-source Platform for Multi-modality Foundation Models in Medicine

no code implementations28 Feb 2024 Xiaosong Wang, Xiaofan Zhang, Guotai Wang, Junjun He, Zhongyu Li, Wentao Zhu, Yi Guo, Qi Dou, Xiaoxiao Li, Dequan Wang, Liang Hong, Qicheng Lao, Tong Ruan, Yukun Zhou, Yixue Li, Jie Zhao, Kang Li, Xin Sun, Lifeng Zhu, Shaoting Zhang

The emerging trend of advancing generalist artificial intelligence, such as GPTv4 and Gemini, has reshaped the landscape of research (academia and industry) in machine learning and many other research areas.

Transfer Learning

Neural Network Diffusion

2 code implementations20 Feb 2024 Kai Wang, Dongwen Tang, Boya Zeng, Yida Yin, Zhaopan Xu, Yukun Zhou, Zelin Zang, Trevor Darrell, Zhuang Liu, Yang You

The autoencoder extracts latent representations of a subset of the trained neural network parameters.

Decoder

Expectation Maximization Pseudo Labels

1 code implementation2 May 2023 MouCheng Xu, Yukun Zhou, Chen Jin, Marius de Groot, Daniel C. Alexander, Neil P. Oxtoby, Yipeng Hu, Joseph Jacob

In the remainder of the paper, we showcase the applications of pseudo-labelling and its generalised form, Bayesian Pseudo-Labelling, in the semi-supervised segmentation of medical images.

Segmentation

Progressive Subsampling for Oversampled Data -- Application to Quantitative MRI

1 code implementation17 Mar 2022 Stefano B. Blumberg, Hongxiang Lin, Francesco Grussu, Yukun Zhou, Matteo Figini, Daniel C. Alexander

We build upon a recent dual-network approach that won the MICCAI MUlti-DIffusion (MUDI) quantitative MRI measurement sampling-reconstruction challenge, but suffers from deep learning training instability, by subsampling with a hard decision boundary.

Deep Learning Neural Architecture Search

VAFO-Loss: VAscular Feature Optimised Loss Function for Retinal Artery/Vein Segmentation

no code implementations12 Mar 2022 Yukun Zhou, MouCheng Xu, Yipeng Hu, Stefano B. Blumberg, An Zhao, Siegfried K. Wagner, Pearse A. Keane, Daniel C. Alexander

Estimating clinically-relevant vascular features following vessel segmentation is a standard pipeline for retinal vessel analysis, which provides potential ocular biomarkers for both ophthalmic disease and systemic disease.

Segmentation

MisMatch: Calibrated Segmentation via Consistency on Differential Morphological Feature Perturbations with Limited Labels

2 code implementations23 Oct 2021 Mou-Cheng Xu, Yukun Zhou, Chen Jin, Marius de Groot, Neil P. Oxtoby, Daniel C. Alexander, Joseph Jacob

The state-of-the-art SSL methods in image classification utilise consistency regularisation to learn unlabelled predictions which are invariant to input level perturbations.

Decoder Image Classification +5

Learning to Address Intra-segment Misclassification in Retinal Imaging

2 code implementations25 Apr 2021 Yukun Zhou, MouCheng Xu, Yipeng Hu, Hongxiang Lin, Joseph Jacob, Pearse A. Keane, Daniel C. Alexander

Accurate multi-class segmentation is a long-standing challenge in medical imaging, especially in scenarios where classes share strong similarity.

Retinal Vessel Segmentation Segmentation

Deep learning to estimate the physical proportion of infected region of lung for COVID-19 pneumonia with CT image set

no code implementations9 Jun 2020 Wei Wu, Yu Shi, Xukun Li, Yukun Zhou, Peng Du, Shuangzhi Lv, Tingbo Liang, Jifang Sheng

For the segmented masks of intact lung and infected regions, the best method could achieve 0. 972 and 0. 757 measure in mean Dice similarity coefficient on our test benchmark.

Computed Tomography (CT) Prognosis

A Refined Equilibrium Generative Adversarial Network for Retinal Vessel Segmentation

no code implementations26 Sep 2019 Yukun Zhou, Zailiang Chen, Hailan Shen, Xianxian Zheng, Rongchang Zhao, Xuanchu Duan

In this work, we present an end-to-end synthetic neural network, containing a symmetric equilibrium generative adversarial network (SEGAN), multi-scale features refine blocks (MSFRB), and attention mechanism (AM) to enhance the performance on vessel segmentation.

Computational Efficiency Generative Adversarial Network +2

Dual-attention Focused Module for Weakly Supervised Object Localization

no code implementations11 Sep 2019 Yukun Zhou, Zailiang Chen, Hailan Shen, Qing Liu, Rongchang Zhao, Yixiong Liang

In each branch, the input feature map is deduced into an enhancement map and a mask map, thereby highlighting the most discriminative parts or hiding them.

Object Object Recognition +2

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