| FazBrowse GitHub Viewer | Trending | | Home |
| Tools: [Original HTTPS Page] |
Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.
You must be logged in to block users.
Contact GitHub support about this userโs behavior. Learn more about reporting abuse.
Report abuseI also bring strong expertise in computer vision, particularly in object detection, robustness evaluation, and handling data and model drift in real-world production environments. I regularly translate business requirements into technical roadmaps, mentor engineers and data scientists, and ensure that research ideas are converted into reliable, high-impact production systems.
SONY India Software Center (Machine Learning Engineer):
At SONY, I developed an end-to-end pose detection pipeline in C++ from Python, utilizing the Pytorch framework for bitwise serialization and ONNX for inference. This project significantly advanced the company's computer vision capabilities.
Stealth Start-up (Data Scientist):
I researched model drift and anomaly detection for vision data using generative techniques like GAN and VAE. My work included evaluating model performance using statistical methods, developing data visualization pipelines, and performing A/B testing to assess solution effectiveness.
This model is created using pre-trained CNN architecture (VGG16 and RESNET50) via Transfer Learning that classifies the Waste or Garbage material (class labels =7) for recycling.
There are several different types of traffic signs like speed limits, no entry, traffic signals, turn left or right, children crossing, no passing of heavy vehicles, etc. Traffic signs classificatiโฆ
Agentic ai based retail analytics dashboard
HIV molecules inhibitor classification using GNN with attention
A scalable solution using VGG16 for feature extraction from chest X-rays and a kNN-SVM hybrid model for classification.
Python 1
Semantic Segmentation using Unet
Python 1
| Back | FazBrowse Home | New Git URL |