I'm experienced in various programming languages and hardware design, especially in ML, CV, FPGA and embedded systems.
Check out my LinkedIn profile for more!
π§ DIV2K_SR_chalge β Super-Resolution with ESPCN, CNN NETWORK
- USING CNN & RESIDUAL CONNECTION
π Final project for "Deep Learning in Signal & Image Processing" course
π Compared Vanilla ESPCN, Residual ESPCN, and Ablation (No Global Skip)
π Evaluated on PSNR, SSIM, FID β Residual model performed best
π Built with PyTorch Lightning,piq, DIV2K dataset, Google Colab
- Tech: Python, OpenCV, Embedded Linux
- Description:
Developed a real-time car detection system using a Raspberry Pi and USB camera.
The system uses computer vision to identify vehicles from a live video feed and can be integrated into smart traffic or parking systems. - Skills Applied: Embedded systems, image processing, hardware interfacing, and real-time debugging.
- Verilog HDL Projects
- Final B.Sc EE Project
Face Detection using XML-based classifiers on FPGA
- Python
- Digit Detection using Neural Networks
- Rush Hour Game (OOP)
- 4 In Line Game (OOP)
- X/O Game (OOP)