M.Sc.

Yuli Wu

Wissenschaftlicher Mitarbeiter

 106
 +49 241 80 27974
 +49 241 80 22200
 yuli.wu@lfb.rwth-aachen.de



Curriculum Vitae

Jul 2021 – heute Wissenschaftlicher Mitarbeiter, Lehrstuhl für Bildverarbeitung, RWTH Aachen
Sep 2020 – Mär 2021 Praktikum bei SAP SE
Okt 2018 – Mär 2021 M. Sc. Elektrotechnik, Informationstechnik & Technische Informatik, RWTH Aachen
Okt 2015 – Sep 2018 B. Sc. Elektrotechnik, Informationstechnik & Technische Informatik, RWTH Aachen

 


Forschungsgebiet

Computer Vision in Netzhautschnittstellen durch Deep Learning

Veröffentlichungen

 

2024

Yuli Wu, Weidong He, Dennis Eschweiler, Ningxin Dou, Zixin Fan, Shengli Mi, Peter Walter and Johannes Stegmaier
Retinal OCT Synthesis with Denoising Diffusion Probabilistic Models for Layer Segmentation
In: IEEE 21st International Symposium on Biomedical Imaging (ISBI)

2023

Long Chen, Yuli Wu, Johannes Stegmaier and Dorit Merhof
SortedAP: Rethinking Evaluation Metrics for Instance Segmentation
In: ICCV Workshop on BioImage Computing

2023

Yuli Wu, Laura Koch, Peter Walter and Dorit Merhof
Abstract: Convolutional Neural Network-based Inverse Encoder for Optimization of Retinal Prosthetic Stimulation
In: The Artificial Vision Symposium – The International Symposium on Visual Prosthetics

2023

Yuli Wu, Ivan Karetic, Johannes Stegmaier, Peter Walter and Dorit Merhof
A Deep Learning-based in silico Framework for Optimization on Retinal Prosthetic Stimulation
In: International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

2022

Long Chen, Yuli Wu and Dorit Merhof
Instance Segmentation of Dense and Overlapping Objects via Layering
In: The British Machine Vision Conference (BMVC)

2022

Reza Azad, Moein Heidari, Yuli Wu and Dorit Merhof
Contextual Attention Network: Transformer Meets U-Net
In: MICCAI Workshop on Machine Learning in Medical Imaging (MLMI 2022)

2022

Yuli Wu, Peter Walter and Dorit Merhof
Multiscale Softmax Cross Entropy for Fovea Localization on Color Fundus Photography
In: Bildverarbeitung fuer die Medizin (BVM)

2021 Yuli Wu, Yucheng Hu, Suting Miao
Object Detection Based Handwriting Localization
In: ICDAR Workshop on Industrial Applications of Document Analysis and Recognition

 

2020

Yuli Wu, Long Chen and Dorit Merhof
Improving Pixel Embedding Learning through Intermediate Distance Regression Supervision for Instance Segmentation
In: ECCV Workshop on Computer Vision Problems in Plant Phenotyping

2020

Long Chen, Weiwen Zhang, Yuli Wu, Martin Strauch and Dorit Merhof
Semi-supervised Instance Segmentation with a Learned Shape Prior
In: MICCAI Workshop on Medical Image Learning with Less Labels and Imperfect Data (MIL3ID)

 


Lehre

Praktikum: Laboratory Machine Learning (Masterniveau) seit Sommersemester 2021

Betreute Abschlussarbeiten und HiWis:

  • Weidong He: OCT data generation with denoising diffusion probabilistic models for layer segmentation (Mini Thesis, co-supervised with WZL, ongoing)
  • Yunmai Yao: Visual field prediction with optical coherence tomography images via retinal layer segmentation (Bachelor Thesis, ongoing)
  • Julian Wittmann: Optimization of the stimulation pattern for retinal implants using invertible neural networks (Master Thesis, ongoing)
  • David Dziuba: Embedding-based pixel-wise contrastive learning for panoptic segmentation using convolutional neural networks (Master Thesis, ongoing)
  • Ivan Karetic: Optimization of retinal prosthetic stimulation using deep learning techniques (HiWi)
  • Laura Koch: Model-aware optimization of retinal prosthetic stimulation on static grayscale images using pulse2percept (Bachelor Thesis, co-supervised with Chair of Software Engineering)
  • Dahan Wang: Layer segmentation and glaucoma detection on optical coherence tomography images using deep learning (Master Thesis)
  • Zidong Liu: Circular sectoral anchors for leaf segmentation with Mask R-CNN (Master Thesis)
  • Jona Schulz: Supervised cross-image pixelwise contrastive learning for semantic segmentation on Cityscapes (Bachelor Thesis); OCT layer segmentation with standard Transformers (HiWi)
  • Qianru Cai: Visual explanation of eye disease classification on fundus images using generative adversarial networks (Master Thesis)
  • Chendi Zhu: Improving semantic segmentation with contrastive learning on Cityscapes through neural architecture search (Master Thesis)
  • Emre Özcanoğlu: Loss balancing for multitask learning on fundus images with shared representations (Master Thesis)
  • Niklas Demel: Fovea localization on fundus images including prior knowledge about the location of the optic disc using deep learning (Bachelor Thesis)
  • Niels Etschenberg: Questionnaires with visually impaired subjects (HiWi, collaborated with Department of Ophthalmology)

   Wenn eines der oben genannten Themen Ihr Interesse für eine Abschlussarbeit weckt, senden Sie mir bitte eine E-Mail mit Ihrem Lebenslauf und Notenspiegel.