Following Jean-Yves’ inspiring testimonial
@jytinevez, I’m pleased to share some backstory chapters of the JDLL project! While the idea had been brewing in our minds for quite some time, it truly gained momentum during my UC3M Chair of Excellence stay at Arrate's lab
@ArrateMunoz in Madrid in fall 2021. It was a stimulating period as Estibaliz
@gomez_mariscal had just read her PhD thesis, and their remarkable deepImageJ
@deepImageJ paper had been published in Nature Methods, acting as a catalyst for the Icy team to channel their time and energy into deepIcy. We were fortunate that Carlos
@carlosg91018370, a talented developer with a wealth of experience in deepImageJ, was both available and keen on pushing the boundaries of Java libraries for deep learning in bioimaging. Collaborating with Stéphane, they embarked on a complete redesign of the initial deepIcy
@deepIcy_IP prototype that would become JDLL, incorporating cutting-edge advancements in Java/Python interfaces and more. Now, the rest of the story is in your hands, as we present you with the tools to shape the future of deep learning for bioimaging data analysis. Be creative and have fun!
Jean-Christophe
Quick personal story thread about this work -
A few years ago we were working with Jean-Christophe on a prototype of Icy3. We wanted to get closer to the ImageJ ecosystem, and in particular join the community effort in making Deep-Learning easily accessible to biologists.