Samuel Alexander / Edge AI Recycle Bin Public
Target: Arduino Nano 33 BLE Sense (Cortex-M4F 64MHz) Clone this project
Impulses 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

Arduino Nano 33 BLE Sense (Cortex-M4F 64MHz)

100 ms

256 kB

1024 kB

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F1-score

Precision

Recall

98%
spectr-conv1d-e57
Show logs
PERFORMANCE
LATENCY
115 ms of 100 ms
Exceeds target by 15 ms
RAM
24 kB of 256 kB
ROM
40 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
250 ms |
Enabled

SPECTROGRAM

0.05 | 0.025 | -72

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 98%

Type Filters Kernel Rate
conv1d 16 3 -
conv1d 32 3 -
conv1d 64 3 -
dropout - - 0.5

6/26/2023, 6:26:55 AM

98%
mfe-conv1d-fce
Show logs
PERFORMANCE
LATENCY
222 ms of 100 ms
Exceeds target by 122 ms
RAM
20 kB of 256 kB
ROM
66 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
250 ms |
Enabled

MFE

0.02 | 0.02 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 98%

Type Filters Kernel Rate
conv1d 16 3 -
conv1d 32 3 -
conv1d 64 3 -
conv1d 128 3 -
dropout - - 0.25

6/26/2023, 6:32:47 AM

98%
mfe-conv1d-b96
Show logs
PERFORMANCE
LATENCY
227 ms of 100 ms
Exceeds target by 127 ms
RAM
20 kB of 256 kB
ROM
31 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
250 ms |
Enabled

MFE

0.032 | 0.016 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 98%

Type Filters Kernel Rate
Data augmentation
conv1d 8 3 -
conv1d 16 3 -
conv1d 32 3 -
dropout - - 0.5

6/26/2023, 6:33:54 AM

96%
spectr-conv1d-769
Show logs
PERFORMANCE
LATENCY
130 ms of 100 ms
Exceeds target by 30 ms
RAM
23 kB of 256 kB
ROM
42 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
250 ms |
Enabled

SPECTROGRAM

0.05 | 0.025 | -32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 96%

Type Filters Kernel Rate
Data augmentation
conv1d 32 3 -
conv1d 64 3 -
dropout - - 0.25

6/26/2023, 6:23:09 AM

96%
spectr-conv1d-b47
Show logs
PERFORMANCE
LATENCY
231 ms of 100 ms
Exceeds target by 131 ms
RAM
39 kB of 256 kB
ROM
72 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

SPECTROGRAM

0.025 | 0.0125 | -32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 96%

Type Filters Kernel Rate
conv1d 32 3 -
conv1d 64 3 -
conv1d 128 3 -
dropout - - 0.5

6/26/2023, 6:23:33 AM

96%
spectr-conv1d-ea6
Show logs
PERFORMANCE
LATENCY
51 ms of 100 ms
RAM
15 kB of 256 kB
ROM
40 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
500 ms |
Enabled

SPECTROGRAM

0.075 | 0.075 | -52

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 96%

Type Filters Kernel Rate
Data augmentation
conv1d 32 3 -
conv1d 64 3 -
dropout - - 0.25

6/26/2023, 6:26:44 AM

96%
mfe-conv1d-60e
Show logs
PERFORMANCE
LATENCY
241 ms of 100 ms
Exceeds target by 141 ms
RAM
19 kB of 256 kB
ROM
67 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
250 ms |
Enabled

MFE

0.02 | 0.02 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 96%

Type Filters Kernel Rate
Data augmentation
conv1d 32 3 -
conv1d 64 3 -
conv1d 128 3 -
dropout - - 0.25

6/26/2023, 6:31:53 AM

96%
spectr-conv1d-1c1
Show logs
PERFORMANCE
LATENCY
66 ms of 100 ms
RAM
16 kB of 256 kB
ROM
41 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
500 ms |
Enabled

SPECTROGRAM

0.05 | 0.05 | -72

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 96%

Type Filters Kernel Rate
conv1d 32 3 -
conv1d 64 3 -
dropout - - 0.5

6/26/2023, 6:27:13 AM

96%
spectr-conv1d-fd0
Show logs
PERFORMANCE
LATENCY
63 ms of 100 ms
RAM
16 kB of 256 kB
ROM
41 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
500 ms |
Enabled

SPECTROGRAM

0.05 | 0.05 | -32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 96%

Type Filters Kernel Rate
conv1d 32 3 -
conv1d 64 3 -
dropout - - 0.25

6/26/2023, 6:29:16 AM

96%
spectr-conv2d-9c7
Show logs
PERFORMANCE
LATENCY
115 ms of 100 ms
Exceeds target by 15 ms
RAM
21 kB of 256 kB
ROM
34 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

SPECTROGRAM

0.075 | 0.075 | -52

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 96%

Type Filters Kernel Rate
conv2d 8 3 -
conv2d 16 3 -
conv2d 32 3 -
dropout - - 0.25

6/26/2023, 6:31:41 AM

96%
spectr-conv1d-2f2
Show logs
PERFORMANCE
LATENCY
59 ms of 100 ms
RAM
17 kB of 256 kB
ROM
39 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

SPECTROGRAM

0.05 | 0.05 | -72

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 96%

Type Filters Kernel Rate
Data augmentation
conv1d 16 3 -
conv1d 32 3 -
conv1d 64 3 -
dropout - - 0.25

6/26/2023, 6:32:12 AM

96%
spectr-conv2d-702
Show logs
PERFORMANCE
LATENCY
155 ms of 100 ms
Exceeds target by 55 ms
RAM
21 kB of 256 kB
ROM
34 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
250 ms |
Enabled

SPECTROGRAM

0.075 | 0.075 | -52

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 96%

Type Filters Kernel Rate
conv2d 8 3 -
conv2d 16 3 -
conv2d 32 3 -
dropout - - 0.25

6/26/2023, 6:36:07 AM

96%
spectr-conv1d-fcb
Show logs
PERFORMANCE
LATENCY
71 ms of 100 ms
RAM
19 kB of 256 kB
ROM
31 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

SPECTROGRAM

0.075 | 0.0375 | -32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 96%

Type Filters Kernel Rate
Data augmentation
conv1d 8 3 -
conv1d 16 3 -
conv1d 32 3 -
dropout - - 0.5

6/26/2023, 6:36:05 AM

96%
spectr-conv1d-c3b
Show logs
PERFORMANCE
LATENCY
80 ms of 100 ms
RAM
21 kB of 256 kB
ROM
28 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
1000 ms |
Enabled

SPECTROGRAM

0.025 | 0.025 | -72

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 96%

Type Filters Kernel Rate
conv1d 8 3 -
conv1d 16 3 -
dropout - - 0.5

6/26/2023, 6:36:03 AM

94%
mfe-conv2d-6b0
Show logs
PERFORMANCE
LATENCY
253 ms of 100 ms
Exceeds target by 153 ms
RAM
28 kB of 256 kB
ROM
34 kB of 1024 kB
DSP NN Unused
TIME-SERIES INPUT

1000 ms |
250 ms |
Enabled

MFE

0.02 | 0.02 | 32

ACCURACY (KERAS)
CLASSIFICATION

0.005 | 100 | 94%

Type Filters Kernel Rate
conv2d 8 3 -
conv2d 16 3 -
dropout - - 0.25

6/26/2023, 6:25:08 AM

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