Achieving 96%+ accuracy on US state classification with a 7-model ensemble strategy
NYU Computer Vision project using Vision Transformers, CLIP, and ensemble techniques to predict geographic locations from street view images.
NYU Computer Vision project using template matching and image processing to detect and identify star constellations in astronomical images. Demonstrates classical CV techniques and their applications.
A deep dive into implementing real-time people detection and tracking using YOLOv8/v10 and DeepSORT, with deployment on Azure cloud platform. This project demonstrates end-to-end ML engineering from model selection to production deployment.
NYU Computer Vision project using Vision Transformers, CLIP, and ensemble techniques to predict geographic locations from street view images.
Hackathon-winning project implementing adaptive computer vision pipeline across edge devices and cloud. Features intelligent workload distribution, low-latency inference, and dynamic model selection using Qualcomm AI technology.
NYU Computer Vision project using template matching and image processing to detect and identify star constellations in astronomical images. Demonstrates classical CV techniques and their applications.
A deep dive into implementing real-time people detection and tracking using YOLOv8/v10 and DeepSORT, with deployment on Azure cloud platform. This project demonstrates end-to-end ML engineering from model selection to production deployment.