Based on our record, AWS DeepLens should be more popular than Scale Nucleus. It has been mentiond 5 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
AWS provides various services for Machine Learning and Artificial Intelligence, including Amazon SageMaker, AWS DeepLens, AWS DeepComposer, Amazon Forecast and more. Familiarize yourself with the services available to determine which ones suit your specific needs. - Source: dev.to / 6 months ago
Take a look at AWS deeplens. You might be able to make something work out of it. https://aws.amazon.com/deeplens/. Source: over 1 year ago
AWS DeepLens - Deep learning enabled video camera for developers - AWS (amazon.com). - Source: dev.to / over 2 years ago
So Amazon has this thing called Deep Lens. Https://aws.amazon.com/deeplens/ Basically, it's a really dinky computer with all the things needed to do Machine Learning with image recognition. It comes with several projects that all are about how to program it, and how to run machine learning enabled image recognition projects (including 'Hotdog-Not A Hotdog'!). It's an expense, but it would enable what you're... Source: over 2 years ago
AWS DeepLens is a hardware offering from AWS. It comes with a fully programmable camera you can use to train Machine Learning models for your specific task. Tutorials and guides also accompany this to get started right away. - Source: dev.to / over 3 years ago
At Scale we built a tool for model debugging in computer vision called Nucleus (scale.com/nucleus) designed exactly for this, which is free try out if you're curious to see where your model predictions are most at odds with your ground truth. Source: over 2 years ago
To address your point about gathering edge cases, which can also be defined as cases of low model fidelity for our use cases, there is active learning and tools such as Aquarium Learning and Scale Nucleus which make it easy to implement into workflows. Source: almost 3 years ago
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