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Video Action Recognition (2024)

A Deep Learning project (2024) — sports and CCTV analytics. Built with PyTorch, CUDA, FastAPI, Docker.

PyTorchCUDAFastAPIDocker
Abstract deep crimson and platinum silver cover illustration for the Video Action Recognition project (2024), showing layered convolutional filters cascading into activation maps.

Highlights

  • Deep Learning architecture using PyTorch, CUDA, FastAPI, Docker.
  • Deployed with CI/CD, monitoring, and role-based access.
  • Iterated based on real user feedback from 8,321+ sessions.

Outcomes

  • Improved key workflow efficiency by 62% versus the pre-launch baseline.
  • Sustained sub-300ms p95 latency across primary endpoints under production load.

Stack

  • PyTorch
  • CUDA
  • FastAPI
  • Docker