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Software implementations of neural network operations using only integer arithmetic to bypass floating-point units.
Distinct from Integer Arithmetic: Focuses on the application of integer math for AI inference rather than general fundamental arithmetic operations.
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This project provides a suite of lightweight face detection models designed for high-speed inference on edge computing devices. It centers on a compact neural network architecture that enables human face detection within environments characterized by limited compute resources and power constraints. The system features quantized face detectors available in multiple formats to ensure compatibility across diverse hardware architectures. It includes utilities for model export and quantization, allowing trained weights to be converted into standardized formats for hardware-agnostic deployment. Th
Uses integer-only arithmetic to accelerate processing on hardware lacking dedicated floating-point units.