I will do real time object detection, tracking and video analytics using yolo

S
s_burhan_ahmed
S
s_burhan_ahmed
Burhan Ahmed

About this gig

I design and build real-time computer vision systems object detection, multi-object tracking, and visual search using YOLO, OpenCV, and modern detection architectures.

Recent work:

InsightVision offline AI surveillance platform combining zero-shot detection (Grounding DINO), segmentation (SAM3), and Kalman-filter tracking (BoT-SORT), running real-time on a single GPU.

Real-Time Fall Detection published paper (IEEE ICIC 2025), YOLOv11-based elderly safety monitoring.

CelebVision YOLOv11 + EfficientNetV2 pipeline, 1st place in a Computer Vision Kaggle competition.

What I can build for you:

Custom object detection models (fine-tuned YOLO or zero-shot, your classes)

Multi-object tracking across video feeds (ID-consistent, not just per-frame)

Real-time inference pipelines wrapped as an API (FastAPI)

Video analytics: counting, zone alerts, activity logging

Stack: Python, PyTorch, OpenCV, FastAPI. Clean, documented code you're not locked into me for every future tweak.

Message me with your dataset/use case before ordering so I can confirm scope and timeline.

Get to know Burhan Ahmed

Burhan Ahmed

Computer Vision and AI Engineer

  • FromPakistan
  • Member sinceSep 2026
  • Avg. response time1 hour
  • Languages

    English
I build production-ready AI systems like computer vision pipelines, conversational agents, and ML-powered automation for businesses that need working software, not prototypes. My computer vision work is IEEE-published (ICIC 2025, real-time fall detection, 95% accuracy, 25 FPS) and spans detection, tracking, and vision-language models. At OptimusFox I cut a production recommendation system's latency from ~5 seconds to under 100ms and built a natural-language agent handling real booking traffic. I design with production constraints in mind like latency & reliability, not just benchmark accuracy.

Related tags