Hackathon: Deep Learning in Java
Human Technopole Milan, ItalyHackathon focused on improving the accessibility of Deep Learning models in Java-based image analysis software tools.
Hackathon focused on improving the accessibility of Deep Learning models in Java-based image analysis software tools.
Wondering how to make the most out of your bioimaging data?
Join us for a free, online workshop that will introduce the FAIR (Findable, Accessible, Interoperable and Reusable) principles, focusing on their implementation for bioimaging data.
Speakers will include representatives from Euro-BioImaging, BioImage Archive, the AI4Life project, and more … Our special guest, Katrín Möller, a post-doctoral researcher at Biomedical Center of the University of Iceland, will share her personal story of depositing her microglia dataset on the BioImage Archive.
The Open Symposium will start on Thursday the 11th of May and will focus on recent scientific developments and open tools in bioimage analysis. There will be a special session for AI4Life, covering Deep Learning-related topics. More information about the Open Symposium can be found here.
AI4Life and the BioImage Model Zoo (Anna Kreshuk).
The Defragmentation Training School 2 is addressed to the new generation of bioimage analysts and will take place from the 8th to the 12th of May 2023. The training school is supported by EOSC-Life, Euro-BioImaging, AI4Life and i3S.More information about the Defragmentation Training School can be found here.
The course is designed to provide an introduction to the fundamentals of machine learning and deep learning, as well as an understanding of when and how these methods are suitable for image analysis. Participants will gain an understanding of software options for image analysis using deep learning without coding experience and the ability to practically […]
The Open Symposium will start on Thursday the 11th of May and will focus on recent scientific developments and open tools in bioimage analysis. There will be a special session for AI4Life, covering Deep Learning-related topics. More information about the Open Symposium can be found here.
This meeting will be the fourth instalment of our highly successful Cell Dynamics Meeting series, and will focus on ‘Imaging Cell Dynamics’. Emphasis will be placed on researchers addressing biological questions using the latest technologies rather than engineers and optical experts developing new microscopes to ensure the meeting still has a cellular focus.
This virtual course will show how public bioimaging data resources, centred around the BioImage Archive, enable and enhance machine learning based image analysis. The content will explore a variety of data types including electron and light microscopy and miscellaneous or multi-modal imaging data at the cell and tissue scale. Participants will cover contemporary biological image […]
This course has two parallel tracks:Early career investigators track: Learn to master the tools and techniques of bioimage analysis for your own research. From power usage to building analysis pipelines.Analysts track: Learn to use and deploy advanced tools; learn to master high-performance computing for advanced bioimage analysis.Both tracks of the course have a specific focus on hands-on and […]
This event brings together the computational and life science communities. We are currently building web and cloud infrastructure aimed at addressing the challenges of building and deploying AI tools for bioimage analysis and making them more scalable and easily accessible from the BioImage Model Zoo.
The advent of deep learning has brought a revolution in the field of computer vision, including most tasks and research questions concerned with microscopy image analysis. Neural networks have been successfully used for image restoration, classification and segmentation, for the detection of objects and characterisation of their morphology, for high-throughput imaging and large-scale processing in […]