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End-to-End deployment of deep learning models for image classification on embedded systems with a comparative study of TensorFlow Lite and PyTorch-ONNX workflows
Angel Naumov, Patricio Bulić
Diplomsko delo
Oznake: embedded system;artificial intelligence;edge compuing;TinyML;STM32;computer and information science;diploma thesis;
This thesis examines the end-to-end deployment of deep learning models for image classification on the STM32H747I-Discovery board, a resource-constrained embedded system. A detailed comparative analysis of two deployment workflows is provided: one using TensorFlow with its native TFLite format and a ...
Leto: 2025 Vir: Fakulteta za računalništvo in informatiko (UL FRI)
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