Leonardo Alchieri

Orcid: 0000-0003-3088-6132

According to our database1, Leonardo Alchieri authored at least 9 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Lateralization Effects in Electrodermal Activity Data Collected Using Wearable Devices.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., March, 2024

2023
BiHeartS: Bilateral Heart Rate from multiple devices and body positions for Sleep measurement Dataset.
CoRR, 2023

Video-Based Emotion Estimation Using Deep Neural Networks: A Comparative Study.
Proceedings of the Image Analysis and Processing - ICIAP 2023 Workshops, 2023

Enhancing XGBoost with Heuristic Smoothing for Transportation Mode and Activity Recognition.
Proceedings of the Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing, 2023

Recognition of Engagement from Electrodermal Activity Data Across Different Contexts.
Proceedings of the Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing, 2023

2022
Heart Rate During Sleep Measured Using Finger-, Wrist- and Chest-Worn Devices: A Comparison Study.
Proceedings of the Pervasive Computing Technologies for Healthcare, 2022

On the mismatch between measured and perceived sleep quality.
Proceedings of the Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2022 ACM International Symposium on Wearable Computers, 2022

On the Impact of Lateralization in Physiological Signals from Wearable Sensors.
Proceedings of the Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2022 ACM International Symposium on Wearable Computers, 2022

2021
An introduction to quantum machine learning: from quantum logic to quantum deep learning.
Quantum Mach. Intell., 2021


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