Info

Not only does this project review the intricate fundamentals of Convolutional Neural Networks, but it also accomplishes an applicational implementation of plant disease detection on a DE10 FPGA via the use of a fully custom MobileNet V1 implementation on raw Python libraries.

With the aid of more than 30+ papers reviewed - An exploration into the practical methods used to attempt such an implementation was a heavy priority for a feasible implementation plan.

Covers

1. Applicational requirements & constraints
2. CNN fundamentals & Building blocks review
3. CNN platform review
4. CNN and DepthWiseConvolution review, comparison & analysis
5. Model training practices
6. Custom Python implementation
7. System functional simulation
8. Custom single purpose processor for matrix multiplication
9. Avalon MM interfaces
10. Custom peripheral
11. System implementation

Contains

1. Comprehensive documentation and block diagrams
2. Full practical src code (Python/C/VHDL)
3. Full theortical material (Reports/Presentations/Diagrams/Documentation)
4. Modular based implementation for free use & to advance fundamental understanding of the covered topics