EON Tuner
The EON Tuner helps you find the most optimal architecture for your embedded machine-learning application. Clone this project to use the EON Tuner.
Target
No name set
Vision
Arduino Nano 33 BLE Sense (Cortex-M4F 64MHz)
100 ms
256 kB
1024 kB
Filters
Status
DSP type
Network type
View
Data set
Precision
Sort
General
F1-score
Precision
Recall
PERFORMANCE
LATENCY
101 ms of
100 ms
Exceeds target by 1 ms
RAM
17 kB of
256 kB
ROM
33 kB of
1024 kB
DSP
NN
Unused
INPUT
32 | 32
IMAGE
Grayscale
ACCURACY
CLASSIFICATION
0.0005 | 10
| Type | Filters | Kernel | Rate |
|---|---|---|---|
| conv2d | 8 | 3 | - |
| conv2d | 16 | 3 | - |
| conv2d | 32 | 3 | - |
| dropout | - | - | 0.25 |
6/23/2023, 3:21:46 PM
Training output
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Click 'Run EON Tuner' to begin
