Image Segmentation API

Customized, Optimized & Scalable AI-Powered, Pixel-Level Image Segmentation By API 

A Collaborative Image Segmentation Platform To Segment And Annotate Images

Semantic Segmentation

DeepLobe’s Image Segmentation models detect objects within the images, pixel-by-pixel rather than with bounding boxes. Our accurate object detection and image labeling capabilities provide more incisive insights in real-time.

Instance Segmentation

The Instance segmentation models of DeepLobe approach an additional object detection step to obtain the individual instances of all classes in an image. Our granular identification of the individual objects provides more accurate data insights.

Instance Segmentation

The Instance segmentation models of DeepLobe approach an additional object detection step to obtain the individual instances of all classes in an image. Our granular identification of the individual objects provides more accurate data insights.

Image Segmentation To Drive Incisive Business Insights

Healthcare

By leveraging Machine Learning and Deep Learning, the  healthcare sector has the potentiality to radically improve the diagnosis to provide better patient outcomes with medical image processing, image fusion, computer-aided diagnosis, image retrieval and analysis, image-guided therapy, etc.

  • Early detection of cancer and cancer cells to provide early diagnosis.
  • Accurate diagnosis of tumors from MRI scans.
  • Detecting physical abnormalities in a body by swiftly processing thousands of images.
  • Image labeling.
image segmentation healthcare Deeplobe
image segmentation autonomous vehicles Deeplobe

Autonomous Vehicles

Pixel-level labeling labels each and every pixel to provide a complete understanding of the image. And hence, image segmentation is the best tool to detect objects across the road-map, real-time identification of pedestrians, vehicles, bicyclists, paths, etc and adds an advantage to smart autonomous vehicles.

  • To determine lanes and signs.
  • Automated parking function.
  • Vehicle, pedestrian, and cyclist location determination.
  • Geospacing and dense vegetation to differentiate between vegetation and terrain.

Autonomous Vehicles

Pixel-level labeling labels each and every pixel to provide a complete understanding of the image. And hence, image segmentation is the best tool to detect objects across the road-map, real-time identification of pedestrians, vehicles, bicyclists, paths, etc and adds an advantage to smart autonomous vehicles.

  • To determine lanes and signs.
  • Automated parking function.
  • Vehicle, pedestrian, and cyclist location determination.
  • Geospacing and dense vegetation to differentiate between vegetation and terrain.
image segmentation autonomous vehicles Deeplobe

Security & Surveillance

The digital image processing and computer vision applications improve the efficiency of security and surveillance techniques to optimize business, governments, and public day-to-day operations like unlocking your phone to transferring funds between two bank accounts, image segmentation has its importance.

  • Face recognition.
  • Fingerprint recognition.
  • Iris recognition.
  • Video surveillance.
  • Video object co-segmentation and action localization.
image segmentation security Deeplobe

HOW IT WORKS

Choose a Model

Browse our model catalog and choose a model that meets your unique needs. Upload your data and get started.

Develop Your Model
Train your selected model with the uploaded data set to identify the defined outcomes and test the accuracy of the model.
Deploy and Run your Model

Integrate the API within your system and run the model to segment your images pixel-by-pixel to drive incisive outcomes.

Get Started With DeepLobe Today

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