Niccolò Marini

National Institutes of Health

United States

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Articles (10)

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2022

Year:

2022

Year:

2022

Year:

2021

Year:

2021

Collaborators (13)

Michael Ignaz Schumacher

Prof. Dr.

University of Applied Sciences and Arts Northwestern Switzerland

SWITZERLAND

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Yazan Mualla

Associate Professor

Université de Technologie de Belfort-Montbéliard

FRANCE

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Henning Müller

Professor

HES-SO

SWITZERLAND

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Alessandro Caputo

ITALY

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Jean-Paul Calbimonte

Associate Professor

University of Applied Sciences and Arts Northwestern Switzerland

SWITZERLAND

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Stephane Marchand-Maillet

Professeur

Université de Genève

SWITZERLAND

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Kimmo Kartasalo

Karolinska Institutet

SWEDEN

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Davide Calvaresi

Associate Professor

HES-SO Valais Wallis

SWITZERLAND

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manfredo atzori

Assistant Professor

University of Padova

ITALY

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Francesco Ciompi

Associate Professor

Radboud University Medical Center

NETHERLANDS

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Jeroen van der Laak

Radboud University Medical Center

NETHERLANDS

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Selene Tomassini

Assistant Professor

Università degli Studi di Torino

ITALY

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Anne-Vibeke Lænkholm

Zealand University Hospital

DENMARK

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Niccolò Marini

Research Interests

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Articles (10)

The ACROBAT 2022 challenge

Multimodal representations of biomedical knowledge from limited training whole slide images and reports using deep learning

A systematic comparison of deep learning methods for Gleason grading and scoring

A Multi-Scale CNN for Transfer Learning in sEMG-Based Hand Gesture Recognition for Prosthetic Devices

Data-driven color augmentation for H&E stained images in computational pathology

A DEXiRE for Extracting Propositional Rules from Neural Networks via Binarization

Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations.

Empowering digital pathology applications through explainable knowledge extraction tools

Combining weakly and strongly supervised learning improves strong supervision in Gleason pattern classification

Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: An experiment on prostate histopathology image classification

Collaborators (13)

Michael Ignaz Schumacher

Yazan Mualla

Henning Müller

Alessandro Caputo

Jean-Paul Calbimonte

Stephane Marchand-Maillet

Kimmo Kartasalo

Davide Calvaresi

manfredo atzori

Francesco Ciompi

Jeroen van der Laak

Selene Tomassini

Anne-Vibeke Lænkholm

Make your next move.

Niccolò Marini

Research Interests

Explore related searches

Contact this professor

Articles (10)

The ACROBAT 2022 challenge

Multimodal representations of biomedical knowledge from limited training whole slide images and reports using deep learning

A systematic comparison of deep learning methods for Gleason grading and scoring

A Multi-Scale CNN for Transfer Learning in sEMG-Based Hand Gesture Recognition for Prosthetic Devices

Data-driven color augmentation for H&amp;E stained images in computational pathology

A DEXiRE for Extracting Propositional Rules from Neural Networks via Binarization

Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations.

Empowering digital pathology applications through explainable knowledge extraction tools

Combining weakly and strongly supervised learning improves strong supervision in Gleason pattern classification

Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: An experiment on prostate histopathology image classification

Collaborators (13)

Michael Ignaz Schumacher

Yazan Mualla

Henning Müller

Alessandro Caputo

Jean-Paul Calbimonte

Stephane Marchand-Maillet

Kimmo Kartasalo

Davide Calvaresi

manfredo atzori

Francesco Ciompi

Jeroen van der Laak

Selene Tomassini

Anne-Vibeke Lænkholm

Make your next move.

Data-driven color augmentation for H&E stained images in computational pathology