Mukesh Sankhla / Slot Occupancy Public
Target: Arduino UNO Q (Qualcomm QRB2210) Clone this project

Test data

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Model variants
No additional model variants available Test 'Unoptimized (float32)' model
Set the 'expected outcome' for each sample to the desired outcome to automatically score the impulse.

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Sample name Expected outcome Accuracy Result
PCBA_WIN_20260928_09_47_52_Pro PCBA 100% PCBA
Show classification Show in data acquisition Show in feature explorer
PCBA_WIN_20260928_09_47_46_Pro PCBA 100% PCBA
Show classification Show in data acquisition Show in feature explorer
PCBA_WIN_20260928_09_46_45_Pro PCBA 100% PCBA
Show classification Show in data acquisition Show in feature explorer
PCBA_WIN_20260928_09_46_38_Pro PCBA 100% PCBA
Show classification Show in data acquisition Show in feature explorer
PCBA_WIN_20260928_09_44_04_Pro PCBA 100% PCBA
Show classification Show in data acquisition Show in feature explorer
PCBA_WIN_20260928_09_43_29_Pro PCBA 100% PCBA
Show classification Show in data acquisition Show in feature explorer
PCB_WIN_20260928_09_52_44_Pro PCB 100% PCB
Show classification Show in data acquisition Show in feature explorer
PCB_WIN_20260928_09_52_40_Pro PCB 100% PCB
Show classification Show in data acquisition Show in feature explorer
PCB_WIN_20260928_09_52_36_Pro PCB 100% PCB
Show classification Show in data acquisition Show in feature explorer
PCB_WIN_20260928_09_52_35_Pro PCB 100% PCB
Show classification Show in data acquisition Show in feature explorer
PCB_WIN_20260928_09_51_45_Pro PCB 100% PCB
Show classification Show in data acquisition Show in feature explorer
Empty_WIN_20260928_09_50_15_Pro Empty 100% Empty
Show classification Show in data acquisition Show in feature explorer
Empty_WIN_20260928_09_50_05_Pro Empty 100% Empty
Show classification Show in data acquisition Show in feature explorer
Empty_WIN_20260928_09_49_13_Pro Empty 100% Empty
Show classification Show in data acquisition Show in feature explorer
Empty_WIN_20260928_09_49_12_Pro Empty 100% Empty
Show classification Show in data acquisition Show in feature explorer
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Model testing output

Results

Model version:
Accuracy
100.00%

Metrics for Pretrained learn

Metric Value
Area under ROC Curve 1.00
Weighted average Precision 1.00
Weighted average Recall 1.00
Weighted average F1 score 1.00

Confusion matrix

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Feature explorer

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