Skip to content

Final semester research paper analyzing Quantum CNNs vs. ResNet-50 for medical image classification, developed under deadline pressure using AI-assisted coding tools and neural architecture optimizers. Submitted as coursework to demonstrate quantum-classical hybrid vs. traditional CNN efficacy in diagnostic imaging.

License

Notifications You must be signed in to change notification settings

Harshyadv/Final_Semester_Research_QCNN_vs_ResNet

Repository files navigation

πŸ“š Final Semester Research Paper

QCNN vs. ResNet(50) for Medical Image Classification

This repository contains my final semester research paper that presents a comparative study between Quantum Convolutional Neural Networks (QCNN) and ResNet(50)-based architectures for medical image classification.


πŸ“₯ Download

⬇ Download the Full Paper


πŸ† Achievement

This research paper played a significant role in helping me achieve a 10.0 SGPA in my final semester.


πŸ“Œ Notes

  • Purpose: Submitted as part of my final semester project.
  • Not Published: This work was not published by the university.
  • Timeline: Completed within one week under a strict deadline.
  • AI Assistance: Used AI tools for structuring and refining content.
  • Read-Only: This repository is for archival purposes only. No contributions or modifications will be accepted.

πŸ–‹οΈ Author

Harsh Yadav


βš–οΈ License

This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0).

  • Free to read and share (with credit)
  • Not for commercial use

Β© 2025 Harsh Yadav

About

Final semester research paper analyzing Quantum CNNs vs. ResNet-50 for medical image classification, developed under deadline pressure using AI-assisted coding tools and neural architecture optimizers. Submitted as coursework to demonstrate quantum-classical hybrid vs. traditional CNN efficacy in diagnostic imaging.

Topics

Resources

License

Stars

Watchers

Forks

Packages

No packages published