Publication

DeepImageJ: A user-friendly environment to run deep learning models in ImageJ

Michaël Unser, Daniel Sage, Laurène Donati
2021
Journal Articles

Abstract

DeepImageJ offers a user-friendly solution in ImageJ to run trained deep learning models for biomedical image analysis. It includes guiding tools for reliable analyses, contributing to the democratization of deep learning in microscopy.

Official source

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

DeepImageJ: A user-friendly environment to run deep learning models in ImageJ

Chat with Graph Search

Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning

Incorporating Projective Geometry into Deep Learning

Predicting the long-term collective behaviour of fish pairs with deep learning