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Use cases

Overview

H2O Hydrogen Torch enables novice and expert data scientists to solve a large set of diverse problem types in computer vision, natural language, and audio. Below explore a few use case examples that you can solve using H2O Hydrogen Torch.

H2O.ai Catalog

To access the datasets, models, and outputs of 99+ use cases implemented in H2O Hydrogen Torch, see H2O.ai Catalog. The use cases offered in the H2o.ai Catalog cover a range of industries while highlighting how you can utilize your data with H2O Hydrogen Torch.

Image

Image classification/regression

As example use cases, you can build an image classification or regression model in H2O Hydrogen Torch to:

  • Identify pneumonia on chest X-rays
  • Classify the type of landscape from satellite or drone images
  • Predict the sum of coins in images

3D image classification/regression

As example use cases, you can build a 3D image classification or regression model in H2O Hydrogen Torch to:

  • Use 3D X-ray lung images to identify the type or grade of a lesion
  • Use 3D magnetic resonance imaging (MRI) images of the brain to determine the type or grade of a lesion
  • Use 3D computer tomography (CT) spine images to identify fractures

Image object detection

As example use cases, you can build an image object detection model in H2O Hydrogen Torch to:

  • Find abnormalities on chest X-ray images of pneumonia patients
  • Detect vehicles in traffic or drone cameras
  • Detect required pieces during an assembly process

Image semantic segmentation

As example use cases, you can build an image semantic segmentation model in H2O Hydrogen Torch to:

  • Cut out objects from image backgrounds
  • Segment a series of video frames based on a video captured by a dashcam
  • Locate the exact form of an object in medical images

3D image semantic segmentation

As example use cases, you can build a 3D image semantic segmentation model in H2O Hydrogen Torch to:

  • Use 3D X-ray images of lungs to segment in 3D lung areas of a lesion
  • Use 3D magnetic resonance imaging (MRI) images of the brain to segment in 3D areas of a tumor
  • Use 3D computer tomography (CT) images of the spine to segment in 3D areas of the spine (for example, fracture areas)

Image instance segmentation

As example use cases, you can build an image instance segmentation model in H2O Hydrogen Torch to:

  • Segment individual cars, pedestrians, or other objects from a dashcam video
  • Detect and delineate distinct objects of interest in biological images

Image metric learning

As example use cases, you can build an image metric learning model in H2O Hydrogen Torch to:

  • Search for identical products on an e-commerce website
  • Search for images with similar landmarks in a database

Text

Text classification/regression

As example use cases, you can build a text classification or regression model in H2O Hydrogen Torch to:

  • Predict customer satisfaction from transcribed phone calls
  • Categorize incoming emails from support@your-company.com and forward them to the appropriate department

Text token classification

As example use cases, you can build a text token classification model in H2O Hydrogen Torch to:

  • Extract entities such as drugs or diseases from medical text
  • Named entity extraction (name, location, etc.)

Text span prediction

As example use cases, you can build a text span prediction model in H2O Hydrogen Torch to:

  • Find relevant information from medical transcripts
  • Build a company-specific question-answering system

Text sequence to sequence

As example use cases, you can build a text sequence to sequence model in H2O Hydrogen Torch to:

  • Simplify text which contains domain-specific terms
  • Summarize text for better understanding of its content

Text metric learning

As example use cases, you can build a text metric learning model in H2O Hydrogen Torch to:

  • Detect fake reviews which are similar to each other
  • Find similar questions in a user forum to remove duplicates

Image and text

Image and text classification

As example use cases, you can build an image and text classification model in H2O Hydrogen Torch to:

  • Classify e-commerce products into categories based on the title and image of the product
  • Classify food dishes based on the text of the recipe and the image of the dish

Audio

Audio classification/regression

As example use cases, you can build an audio classification or regression model in H2O Hydrogen Torch to:

  • Detect bird and frog species by using tropical audio recordings
  • Predict the number of different species in audio files

Speech

Speech recognition

As example use cases, you can build a speech recognition model in H2O Hydrogen Torch to:

  • Transcribe call center recordings
  • Transcribe educational lecture videos

Graph

Graph node classification/regression

As example use cases, you can build a graph node classification or regression model in H2O Hydrogen Torch to:

  • Detect fraudulent nodes in a graph.
  • Predict the category of a product in a product co-purchasing network.
  • Categorize papers’ subject areas in a heterogeneous academic graph.
  • Predict the presence of protein functions in a protein-protein interaction network.

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