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real-time-inference

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This project uses YOLO for real-time leukemia detection in blood samples and CNNs for classifying brain hemorrhages in MRI scans. It aims to support faster, more accurate medical diagnostics through deep learning.

  • Updated May 28, 2025
  • Python

Explore a wide range of computer vision projects and documentation covering everything from object detection, image segmentation, and tracking to pose estimation, object counting, and automated annotation. These resources highlight real-world AI applications built with modern models like Ultralytics YOLO, Meta SAM 2, and other vlms

  • Updated Aug 2, 2025

Custom YOLO11m model for detecting and classifying car body damage (99% shattered glass, 96% flat tire detection accuracy)—optimized for high-capacity inference and assistive use in inspection and service workflows like BMW pre-loaner inspections.

  • Updated Jun 1, 2025
  • Jupyter Notebook

This project uses YOLO for real-time leukemia detection in blood samples and CNNs for classifying brain hemorrhages in MRI scans. It aims to support faster, more accurate medical diagnostics through deep learning.

  • Updated Jul 13, 2025
  • Python

YOLOv12 Underwater Object Detection is an open-source suite for underwater object detection, built on YOLOv12. It offers an end-to-end pipeline with GPU-accelerated training, customizable data augmentations, real-time inference via Gradio, and support for model export (ONNX & PyTorch).

  • Updated Jun 17, 2025
  • Python

This repository features an image sharpening pipeline using Knowledge Distillation. A high-capacity Restormer acts as the teacher model, while a lightweight Mini-UNet is trained as the student to mimic its performance.

  • Updated Jul 12, 2025
  • Jupyter Notebook

Deep learning system for real-time face mask detection achieving 98.2% accuracy using ResNet18 architecture, PyTorch, and Gradio. Features efficient inference (0.12s), optimized model size (44.7MB), and a balanced dataset of 20,000 images for robust production deployment.

  • Updated May 21, 2025
  • Python

Bachelor Final Year Project exploring real-time speech denoising using machine learning. Compares classical methods (SS, WF, MMSE-LSA) with 5 deep models on spectrogram data, highlighting Conv-TasNet’s effectiveness. Features dataset bucketing, OOM mitigation, and batch evaluation.

  • Updated Jul 22, 2025
  • TeX

The Multilingual AI Customer Support System leverages AWS SageMaker and LORA to build scalable AI-driven solutions that provide multilingual customer support. It integrates machine learning models for real-time responses, ensuring efficient and personalized customer service.

  • Updated Feb 12, 2025
  • Python

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