Luigi29577/phinet-tiny-proof

φNet Tiny — Technical Proof One-Pager

Inventor: Luigi Calcagno
📧 [email protected]
Patent-pending φ-loss + Tiny CNN for True Edge Inference

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✅ What This Shows

φNet Tiny is a custom convolutional neural network with:

• Proprietary φ-loss function for tail-class lift.
• Real ONNX → TensorFlow → TFLite flow.
• Proven microcontroller-friendly footprint.

Tested vs MobileNetV2 using real CIFAR-100 sample.

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📊 Combined Results

Sample: torch.Size([1, 3, 32, 32])
Label: 49 (CIFAR-100)

Metric	φNet Tiny	MobileNetV2
Param Size	0.1148 MB	~13.37 MB
TFLite Size	117.52 KB	Not feasible
φ-loss Output	4.5335	N/A
Inference Time (10 runs)	~0.0094 s	~0.0785 s

✅ φNet Tiny deploys .tflite ~117 KB — runs on STM32, ESP32, Pi Zero.
❌ MobileNetV2 cannot run at MCU scale.

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🔑 Key Points

• Reproducible φ-loss benchmark.
• Fully local inference, no cloud.
• Open pilot opportunities.

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Built & tested by Luigi Calcagno
Contact: [email protected]