04- Contributo in atti di convegno

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04.01 - Contributo in atti di convegno 25081
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Neural Architecture for Tennis Shot Classification on Embedded System

Data analysis has become a common practice in professional and amateur sport activities, to monitor the player state and enhance performance. In tennis, performance analysis requires detecting and recognizing the different types of shots. With the advances in microcontrollers and machine learning algorithms, this topic becomes ever more considerable. We propose a 1-D convolutional neural network (CNN) model and an embedded system based on Arduino-Nano system for real-time shot classification....

Low-Cost, Edge-Cloud, End-to-End System Architecture for Human Activity Data Collection

Research in the Internet of Things (IoT) have paved the way to a new generation of applications and services that collect huge quantities of data from the field and do a significant part of the processing on the edge. This requires availability of efficient and effective methodologies and tools for a workflow spanning from the edge to the cloud. This paper presents a generic, complete workflow and relevant system architecture for field data collection and analysis with a focus on the human ph...

Arduino Nano-Based System for Tennis Shot Classification

Wearable technology has gained significant attention in research and commercial applications, including sports, where data collection and analysis play a crucial role in improving skills. This study focuses on tennis and the real-time classification of main shots, such as forehand, backhand, and serve. While previous studies have utilized machine learning methods for classification, they often relied on cloud or desktop processing. This paper proposes a novel neural architecture for real-time...

A Teacher-Configurable Scoring System for Serious Games

Serious Games (SGs) are versatile tools that entertain while addressing serious issues through digital or analog gameplay. However, ensuring continuous supervision during gameplay can be challenging. To overcome this, we propose a flexible scoring system that automates procedure evaluation, empowering learners and promoting independent skill development. By conceptualizing procedures as ordered actions with specific information, our approach enriches the learning experience, making SGs more e...

YoloP-Based Pre-processing for Driving Scenario Detection

Recognition of driving scenarios is getting ever more relevant in research, especially for assessing performance of advanced driving assistance systems (ADAS) and automated driving functions. However, the complexity of traffic situations makes this task challenging. In order to improve the detection rate achieved through state-of-the-art deep learning models, we have investigated the use of the YoloP fully convolutional neural network architecture as a pre-processing step to extract high-leve...

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