Publications related to HISTOBREAST, a collection of brightfield microscopy images of Haematoxylin and Eosin stained breast tissue

A Practical Influence Approximation for Privacy-Preserving Data Filtering in Federated Learning

Boi Faltings, Ljubomir Rokvic, Panayiotis Danassis

Federated Learning by nature is susceptible to low-quality, corrupted, or even malicious data that can severely degrade the quality of the learned model. Traditional techniques for data valuation cannot be applied as the data is never revealed. We present ...

2023

Towards JPEG AIC part 3: visual quality assessment of high to visually lossless image coding

Touradj Ebrahimi, Evgeniy Upenik, Michela Testolina

Due to the increasing number of pictures captured and stored every day by and on digital devices, lossy image compression has become inevitable to limit the needed storage requirement. As a consequence, these compression methods might introduce some visual ...

SPIE2022

Review of subjective quality assessment methodologies and standards for compressed images evaluation

Touradj Ebrahimi, Michela Testolina

Acquiring and exchanging a large number of pictures has become nowadays a common practice. Therefore, new image compression solutions to optimize the storage resources are in constant demand. In this context, it is essential to have a solid methodology to ...

SPIE2021

QUAREP-LiMi: A community-driven initiative to establish guidelines for quality assessment and reproducibility for instruments and images in light microscopy

Arne Seitz, Andrea Bassi, Antje Keppler

A modern day light microscope has evolved from a tool devoted to making primarily empirical observations to what is now a sophisticated , quantitative device that is an integral part of both physical and life science research. Nowadays, microscopes are fou ...

WILEY2021

Performance Evaluation of Objective Image Quality Metrics on Conventional and Learning-Based Compression Artifacts

Touradj Ebrahimi, Evgeniy Upenik, Michela Testolina

Lossy image compression is a popular, simple and effective solution to reduce the amount of data representing digital pictures. In most lossy compression methods, the reduced volume of data in bits is achieved at the expense of introducing visual artifacts ...

2021

NTIRE 2021 Depth Guided Image Relighting Challenge

Sabine Süsstrunk, Majed El Helou, Ruofan Zhou, Radu Timofte

Image relighting is attracting increasing interest due to its various applications. From a research perspective, image relighting can be exploited to conduct both image normalization for domain adaptation, and also for data augmentation. It also has multip ...

2021

Deep Learning Enables Individual Xenograft Cell Classification in Histological Images by Analysis of Contextual Features

Michaël Unser, Cathrin Brisken, Daniel Sage, Olivier Burri, Martin Weigert, Fabio De Martino, Quentin Juppet

Patient-Derived Xenografts (PDXs) are the preclinical models which best recapitulate inter- and intra-patient complexity of human breast malignancies, and are also emerging as useful tools to study the normal breast epithelium. However, data analysis gener ...

2021

Learning a Unified Blind Image Quality Metric via On-Line and Off-Line Big Training Instances

Daniel Thalmann, Xingyu Xu

In this work, we resolve a big challenge that most current image quality metrics (IQMs) are unavailable across different image contents, especially simultaneously coping with natural scene (NS) images or screen content (SC) images. By comparison with exist ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

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HISTOBREAST, a collection of brightfield microscopy images of Haematoxylin and Eosin stained breast tissue

Aggregating Spatial and Photometric Context for Photometric Stereo

Using raytraverse to render high accuracy images

A Practical Influence Approximation for Privacy-Preserving Data Filtering in Federated Learning

Towards JPEG AIC part 3: visual quality assessment of high to visually lossless image coding

Review of subjective quality assessment methodologies and standards for compressed images evaluation

QUAREP-LiMi: A community-driven initiative to establish guidelines for quality assessment and reproducibility for instruments and images in light microscopy

Performance Evaluation of Objective Image Quality Metrics on Conventional and Learning-Based Compression Artifacts

NTIRE 2021 Depth Guided Image Relighting Challenge

Deep Learning Enables Individual Xenograft Cell Classification in Histological Images by Analysis of Contextual Features

Learning a Unified Blind Image Quality Metric via On-Line and Off-Line Big Training Instances

Graph Chatbot

Chat with Graph Search

Aggregating Spatial and Photometric Context for Photometric Stereo

A Practical Influence Approximation for Privacy-Preserving Data Filtering in Federated Learning

Deep Learning Enables Individual Xenograft Cell Classification in Histological Images by Analysis of Contextual Features

QUAREP-LiMi: A community-driven initiative to establish guidelines for quality assessment and reproducibility for instruments and images in light microscopy

Learning a Unified Blind Image Quality Metric via On-Line and Off-Line Big Training Instances

Performance Evaluation of Objective Image Quality Metrics on Conventional and Learning-Based Compression Artifacts

NTIRE 2021 Depth Guided Image Relighting Challenge

Review of subjective quality assessment methodologies and standards for compressed images evaluation

Towards JPEG AIC part 3: visual quality assessment of high to visually lossless image coding

Using raytraverse to render high accuracy images