Deep learning (9)#
BIDS-lecture-2024#
[‘Robert Haase’]
Licensed CC-BY-4.0
Training resources for Students at Uni Leipzig who want to dive into bio-image data science with Python. The material developed here between April and July 2024.
Tags: Bioimage Analysis, Deep Learning, Microscopy Image Analysis, Python
Content type: Github Repository
Bio-image Data Science#
[‘Robert Haase’]
Licensed CC-BY-4.0
This repository contains training resources for Students at Uni Leipzig who want to dive into bio-image data science with Python.
Tags: Image Data Management, Deep Learning, Microscopy Image Analysis, Python
Content type: Notebook
Bio-image Data Science Lectures @ Uni Leipzig / ScaDS.AI#
[‘Robert Haase’]
Licensed CC-BY-4.0
These are the PPTx training resources for Students at Uni Leipzig who want to dive into bio-image data science with Python. The material developed here between April and July 2024.
Tags: Bioimage Analysis, Deep Learning, Microscopy Image Analysis, Python
Content type: Slides
BioEngine Documentation#
[‘Wei Ouyang’, ‘Nanguage’, ‘Jeremy Metz’, ‘Craig Russell’]
Licensed MIT
BioEngine, a Python package designed for flexible deployment and execution of bioimage analysis models and workflows using AI, accessible via HTTP API and RPC.
Tags: Workflow Engine, Deep Learning, Python
Content type: Documentation
BioImage Archive AI Gallery#
Licensed CC0-1.0
Tags: Bioimage Analysis, Deep Learning
Content type: Collection, Data
FAIRy deep-learning for bioImage analysis#
[‘Estibaliz Gómez de Mariscal’]
Licensed CC-BY-4.0
Introduction to FAIR deep learning. Furthermore, tools to deploy trained DL models (deepImageJ), easily train and evaluate them (ZeroCostDL4Mic and DeepBacs) ensure reproducibility (DL4MicEverywhere), and share this technology in an open-source and reproducible manner (BioImage Model Zoo) are introduced.
Tags: Deep Learning, Fair-Principles, Microscopy Image Analysis
Content type: Slides
Introduction to Deep Learning for Microscopy#
[‘Costantin Pape’]
Licensed MIT
This course consists of lectures and exercises that teach the background of deep learning for image analysis and show applications to classification and segmentation analysis problems.
Tags: Deep Learning, Pytorch, Segmentation, Python
Content type: Notebook
MicroSam-Talks#
[‘Constantin Pape’]
Published 2024-05-23
Licensed CC-BY-4.0
Talks about Segment Anything for Microscopy: computational-cell-analytics/micro-sam. Currently contains slides for two talks:
Overview of Segment Anythign for Microscopy given at the SWISSBIAS online meeting in April 2024 Talk about vision foundation models and Segment Anything for Microscopy given at Human Technopole as part of the EMBO Deep Learning Course in May 2024
Tags: Image Segmentation, Bio-Image Analysis, Deep Learning
Content type: Slides
Microscopy data analysis: machine learning and the BioImage Archive#
[‘Andrii Iudin’, ‘Anna Foix-Romero’, ‘Anna Kreshuk’, ‘Awais Athar’, ‘Beth Cimini’, ‘Dominik Kutra’, ‘Estibalis Gomez de Mariscal’, ‘Frances Wong’, ‘Guillaume Jacquemet’, ‘Kedar Narayan’, ‘Martin Weigert’, ‘Nodar Gogoberidze’, ‘Osman Salih’, ‘Petr Walczysko’, ‘Ryan Conrad’, ‘Simone Weyend’, ‘Sriram Sundar Somasundharam’, ‘Suganya Sivagurunathan’, ‘Ugis Sarkans’]
Licensed CC-BY-4.0
The Microscopy data analysis: machine learning and the BioImage Archive course, which focused on introducing programmatic approaches used in the analysis of bioimage data via the BioImage Archive, ran in May 2023.
Tags: Microscopy Image Analysis, Python, Deep Learning
Content type: Videos, Practicals, Slides