Labellio Beta Release – world’s easiest Deep Learning SaaS for computer vision

Labellio, the easiest deep-learning platform for computer vision is now available at https://www.labell.io/ !!

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We are excited to release Labellio Beta, which lets you easily label your image data to create your own deep-learning intelligence without single line of code.

As we provide deep-learning technology solution to multiple enterprises, we realized that there are couple of bottlenecks when applying the technology to develop highly accurate computer vision classifiers, especially (1) when setting up deep-learning networks and (2) when accurately labelling huge amount of the training data set.

In Labellio, we set up Alpaca’s fine-tuned deep-learning networks on high-speed GPU on the cloud so that you do not have to worry about figuring out how GPU or deep-learning networks work.

Also, we developed our proprietary interface for you to label images as training data set as easily and efficiently as possible.  We combined the automated-learning process into the labelling action so that, as you label your images, Labellio learns from your actions to predict what labels will be put on for upcoming images simultaneously.  Please take a look at the demo video below.

We believe that Labellio will support lots of app developers and researchers to experience deep-learning computer vision technology in a very casual manner.  We designed Labellio so that even non-engineers can create highly accurate computer vision classifiers with ease.  We are looking forward to hearing from you as you develop your unique classifiers and use-cases, please tweet it with #labellio !!

We do not restrict any use of the classifiers developed on Labellio regardless of the commercial use or private use.  However, we greatly appreciate it if you can kindly contribute your use-cases to Labellio by letting us know(hello@alpacadb.com) how you are using it or have used Labellio with below format.

  • Your organization and name
  • Name of your service/product
  • How you are using or have used Labellio
  • If okay for us to talk about your case on our blog posts
  • Your contact email address

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