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SEN-D

SEN-D detects kidney stones in CT scans using a stacked ensemble of three convolutional networks (InceptionV3, InceptionResNetV2 and Xception) combined by a meta-learner. It reaches 98.74% accuracy, and shows Grad-CAM heatmaps so you can see which part of the scan drove each decision. The model runs behind a FastAPI backend with a React frontend.

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Projects by Rafay Ahmad (Bonevane)

Experiments

  • iCalc
  • X&O
  • To Do
  • Weather
  • Autolist
  • Notebox
  • CUDA Neural Net
  • Bridge

Game Dev

  • Inside
  • Orrery
  • Path Tracer
  • Aperture
  • ScalAR

3D & Design

  • Never Settle
  • Living
  • Formula 1
  • Sunset Drive
  • Moon Over the Castle
  • Made by Google

Web Dev

  • Danish's Space
  • Staccato
  • GHMS
  • INF-19
  • SEN-D
  • Spillage
  • REACH