Livoa
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Pricing
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Input
32 x 32 x 1
Convolution
(5x5)
Feature Map
28 x 28 x 6
Subsampling
Convolution
(5x5)
Feature Map
14 x 14 x 6
Subsampling
Convolution
(5x5)
Feature Map
10 x 10 x 16
Feature Map
5 x 5 x 16
Fully connected
120
Fully connected
84
Output
10
Dataset
Raw texture images for training, validation, testing
Software Implementation
- LeNet model (Python + NumPy)
- Training & testing
- Store results
Hardware Implementation
- Convert model (Python to C++)
- Vivado HLS: C++ to RTL
- Vivado HLx: synthesis & bitstream
- Spartan-7 FPGA
Performance Comparison
• Accuracy (CPU vs FPGA)
• Training Time (CPU vs FPGA)
• Hardware Acceleration Validation
cnn
by vaish
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