k
khatri_fahad

Fahad

@khatri_fahad

Computer Vision Engineer, YOLO and Real Time Deployment

Pakistán
Inglés, Urdu
Parte de la información aparece en idioma inglés.
Sobre mí
Computer Vision Engineer specializing in YOLO object detection, real-time deployment, and dataset quality auditing. I build pipelines in PyTorch, OpenCV, YOLO, and TensorRT, including multithreaded real-time systems running at deployment speed on consumer GPUs. Most detection models look strong on paper and fail on real data because the train/test split leaked. I audit for that first, so the numbers I report are the numbers you get. Recent work: PCB solder defect detection, real-time drone tracking on a TensorRT pipeline, and a 22,000 experiment LLM bias audit.... Lee más

Habilidades

k
khatri_fahad
Fahad
desconectado • 
Tiempo medio de respuesta: 7 horas

Revisa mis servicios

Visión Artificial
I will train and deploy custom yolo object detection models in real time
DeUSD 90 / proyectoMás información
Etiquetado y anotación de datos
I will annotate images and video for object detection and segmentation datasets
DeUSD 15 / proyectoMás información

Porfolio

Experiencia laboral

Self_Employed

Computer Vision Engineer

Self Employed

Oct 2024 - Present • 2 yrs

Independent computer vision engineering across detection, deployment, and dataset quality. Built a two-stage PCB solder defect detection pipeline pairing a TensorRT-optimized YOLO detector with a downstream classifier, using custom IoU-based losses for small, low-contrast defects. Built a real-time FPV drone tracking system on a three-thread TensorRT pipeline sustaining deployment-speed frame rates on one consumer GPU. Ran a 22,000-experiment audit of hiring bias across five commercial LLMs. All work uses leakage-controlled dataset splitting and full metric reporting.