We are pleased to announce that our #ZeroCostDL4Mic work is now published!
nature.com/articles/s4146…
And our @github
github.com/HenriquesLab/Z…
#DeepLearning and #Microscopy for all!
For the occasion, I’ve put a small Tweetorial together to explain what this is all about!
Thread 0/7
nature.com/articles/s4146…
And our @github
github.com/HenriquesLab/Z…
#DeepLearning and #Microscopy for all!
For the occasion, I’ve put a small Tweetorial together to explain what this is all about!
Thread 0/7
Thread 1/7
You can implement Deep Learning for microscopy in several ways:
1- Using local resources (fast GPUs)
2- Using cloud-computing
3- Using pre-trained models
We think that (1) is uncommon, and that (3) can be unreliable. So we do (2)!
You can implement Deep Learning for microscopy in several ways:
1- Using local resources (fast GPUs)
2- Using cloud-computing
3- Using pre-trained models
We think that (1) is uncommon, and that (3) can be unreliable. So we do (2)!
Thread 2/7
We built a platform using @GoogleColab and @ProjectJupyter notebooks that can perform training, quality control and prediction, all on the cloud and for free!
All of this dedicated to #microscopy !
We built a platform using @GoogleColab and @ProjectJupyter notebooks that can perform training, quality control and prediction, all on the cloud and for free!
All of this dedicated to #microscopy !
Thread 3/7
We implemented a large range of neural networks from some of the best Deep Learning developer teams in the world for segmentation, object detection, denoising, restauration, super-resolution, image-to-image translation, etc.
We implemented a large range of neural networks from some of the best Deep Learning developer teams in the world for segmentation, object detection, denoising, restauration, super-resolution, image-to-image translation, etc.
Thread 4/7
We provide important features such as Data augmentation and Transfer learning. These allow efficient training of all the networks we provide.
We provide important features such as Data augmentation and Transfer learning. These allow efficient training of all the networks we provide.
Thread 5/7
We put a strong emphasis on providing an easy way to assess model quality and performance. This is important to validate any model.
We put a strong emphasis on providing an easy way to assess model quality and performance. This is important to validate any model.
Thread 6/7
We could not do it on our own and we got help from so many great researchers! Part 1/2
@ChamierLucas
@LaineBioImaging
@Liehuletti
@miCHRIScopy
@DanielKrentzel
@martina_lerche
@sara_mattilalab
@mattilalab
@Kar__El
@seamus_holden
We could not do it on our own and we got help from so many great researchers! Part 1/2
@ChamierLucas
@LaineBioImaging
@Liehuletti
@miCHRIScopy
@DanielKrentzel
@martina_lerche
@sara_mattilalab
@mattilalab
@Kar__El
@seamus_holden
Thread 7/7
We could not do it on our own and we got help from so many great researchers! Part 2/2
@_ahmetcansolak
@sagzehn
@tibuch_
@martinjones78
@loicaroyer
@christlet
@ShechtmanLab
@florianjug
Mike Heilemann
@guijacquemet
@HenriquesLab
We could not do it on our own and we got help from so many great researchers! Part 2/2
@_ahmetcansolak
@sagzehn
@tibuch_
@martinjones78
@loicaroyer
@christlet
@ShechtmanLab
@florianjug
Mike Heilemann
@guijacquemet
@HenriquesLab
#Noise2Void from @sagzehn with some nice live data from iSIM!
SI Thread 1/2
We also quantified the limitations of the approach (using @GoogleColab ) and present where it failed in our hands! Breaking points still allow us to train all our networks efficiently though.
We also quantified the limitations of the approach (using @GoogleColab ) and present where it failed in our hands! Breaking points still allow us to train all our networks efficiently though.
SI Thread 2/2
We also showed that it's possible to use our notebooks on other cloud-based platforms such as @DeepnoteHQ and @FloydHub_ , others are available too !
We also showed that it's possible to use our notebooks on other cloud-based platforms such as @DeepnoteHQ and @FloydHub_ , others are available too !
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