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Trabajo Fin de Máster: Estudio comparativo de un clasificador de imágenes en Raspberry Pi, de forma que se compara el tiempo de la inferencia en la Raspberry Pi con y sin el Neural Compute Stick (NCS). También se estudia como la complejidad de una red neuronal repercute en el tiempo de inferencia y se analiza si los tiempos obtenidos con el NCS …
AI based image classification inspired MobileNet V2 architecture by implementing changes in base architecture and details about using it as a quick response model (proposition) for rapid application as well as comparing it with other models for the same application.
Explore the OpenVINO toolkit, focusing on components like model zoo, inference engine, and model optimizer, and how they can be used to perform deep learning and computer vision tasks.
This includes the basics of AI at the Edge, leverage pre-trained models available with the Intel® Distribution of OpenVINO Toolkit™, convert and optimize other models with the Model Optimizer, and perform inference with the Inference Engine.
Demonstrates how to divide a DL model into multiple IR model files (division) and introduce a simplest way to implement a custom layer works with OpenVINO IR models.