Gabriele Civitarese

Orcid: 0000-0002-8247-2524

According to our database1, Gabriele Civitarese authored at least 47 papers between 2015 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

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Online presence:

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Bibliography

2024
ContextGPT: Infusing LLMs Knowledge into Neuro-Symbolic Activity Recognition Models.
CoRR, 2024

2023
Semantic Loss: A New Neuro-Symbolic Approach for Context-Aware Human Activity Recognition.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., December, 2023

MICAR: multi-inhabitant context-aware activity recognition in home environments.
Distributed Parallel Databases, December, 2023

Federated Clustering and Semi-Supervised learning: A new partnership for personalized Human Activity Recognition.
Pervasive Mob. Comput., January, 2023

Probabilistic knowledge infusion through symbolic features for context-aware activity recognition.
Pervasive Mob. Comput., 2023

Ultrasound detection of subquadricipital recess distension.
Intell. Syst. Appl., 2023

Neuro-Symbolic Approaches for Context-Aware Human Activity Recognition.
CoRR, 2023

SelfAct: Personalized Activity Recognition based on Self-Supervised and Active Learning.
CoRR, 2023

Combining Public Human Activity Recognition Datasets to Mitigate Labeled Data Scarcity.
Proceedings of the 2023 IEEE International Conference on Smart Computing, 2023

Is Querying Users Acceptable for Human Activity Recognition Based on Active Learning?
Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2023

Keynote: Data Scarcity in Sensor-Based Human Activity Recognition.
Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2023

GAJA - Guided self-Acquisition of Joint ultrAsound images.
Proceedings of the Simplifying Medical Ultrasound - 4th International Workshop, 2023

DOMINO: A Dataset for Context-Aware Human Activity Recognition using Mobile Devices.
Proceedings of the 24th IEEE International Conference on Mobile Data Management, 2023

2022
Semi-supervised and personalized federated activity recognition based on active learning and label propagation.
Pers. Ubiquitous Comput., 2022

DeXAR: Deep Explainable Sensor-Based Activity Recognition in Smart-Home Environments.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2022

Knowledge Infusion for Context-Aware Sensor-Based Human Activity Recognition.
Proceedings of the 2022 IEEE International Conference on Smart Computing, 2022

Preliminary Results on Sensitive Data Leakage in Federated Human Activity Recognition.
Proceedings of the 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2022

FedCLAR: Federated Clustering for Personalized Sensor-Based Human Activity Recognition.
Proceedings of the IEEE International Conference on Pervasive Computing and Communications, 2022

Explaining Human Activities Instances Using Deep Learning Classifiers.
Proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics, 2022

2021
POLARIS: Probabilistic and Ontological Activity Recognition in Smart-Homes.
IEEE Trans. Knowl. Data Eng., 2021

Collaborative activity recognition with heterogeneous activity sets and privacy preferences.
J. Ambient Intell. Smart Environ., 2021

Personalized Semi-Supervised Federated Learning for Human Activity Recognition.
CoRR, 2021

Explainable Activity Recognition over Interpretable Models.
Proceedings of the 19th IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2021

The MARBLE Dataset: Multi-inhabitant Activities of Daily Living Combining Wearable and Environmental Sensors Data.
Proceedings of the Mobile and Ubiquitous Systems: Computing, Networking and Services, 2021

2020
SmartWheels: Detecting urban features for wheelchair users' navigation.
Pervasive Mob. Comput., 2020

CAVIAR: Context-driven Active and Incremental Activity Recognition.
Knowl. Based Syst., 2020

ProCAVIAR: Hybrid Data-Driven and Probabilistic Knowledge-Based Activity Recognition.
IEEE Access, 2020

Towards Active Learning Interfaces for Multi-Inhabitant Activity Recognition.
Proceedings of the 2020 IEEE International Conference on Pervasive Computing and Communications Workshops, 2020

Context-Aware Data Association for Multi-Inhabitant Sensor-Based Activity Recognition.
Proceedings of the 21st IEEE International Conference on Mobile Data Management, 2020

2019
<i>newNECTAR</i>: Collaborative active learning for knowledge-based probabilistic activity recognition.
Pervasive Mob. Comput., 2019

Context-driven Active and Incremental Activity Recognition.
CoRR, 2019

Automatic Detection of Urban Features from Wheelchair Users' Movements.
Proceedings of the 2019 IEEE International Conference on Pervasive Computing and Communications, 2019

Human Activity Recognition in Smart-Home Environments for Health-Care Applications.
Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops, 2019

Hybrid data-driven and context-aware activity recognition with mobile devices.
Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers, 2019

2018
HUMAN ACTIVITY RECOGNITION IN SMART-HOME ENVIRONMENTS FOR HEALTH-CARE APPLICATIONS.
PhD thesis, 2018

Modeling and Reasoning with ProbLog: An Application in Recognizing Complex Activities.
Proceedings of the 2018 IEEE International Conference on Pervasive Computing and Communications Workshops, 2018

NECTAR: Knowledge-based Collaborative Active Learning for Activity Recognition.
Proceedings of the 2018 IEEE International Conference on Pervasive Computing and Communications, 2018

2017
Monitoring objects manipulations to detect abnormal behaviors.
Proceedings of the 2017 IEEE International Conference on Pervasive Computing and Communications Workshops, 2017

Behavioral monitoring in smart-home environments for health-care applications.
Proceedings of the 2017 IEEE International Conference on Pervasive Computing and Communications Workshops, 2017

2016
SmartFABER: Recognizing fine-grained abnormal behaviors for early detection of mild cognitive impairment.
Artif. Intell. Medicine, 2016

Analysis of long-term abnormal behaviors for early detection of cognitive decline.
Proceedings of the 2016 IEEE International Conference on Pervasive Computing and Communication Workshops, 2016

Unsupervised recognition of interleaved activities of daily living through ontological and probabilistic reasoning.
Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2016

Let the objects tell what you are doing.
Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2016 ACM International Symposium on Wearable Computers, 2016

2015
Extended Report: Fine-grained Recognition of Abnormal Behaviors for Early Detection of Mild Cognitive Impairment.
CoRR, 2015

Fine-grained recognition of abnormal behaviors for early detection of mild cognitive impairment.
Proceedings of the 2015 IEEE International Conference on Pervasive Computing and Communications, 2015

From lab to life: Fine-grained behavior monitoring in the elderly's home.
Proceedings of the 2015 IEEE International Conference on Pervasive Computing and Communication Workshops, 2015

Demo abstract: Demonstration of the FABER system for fine-grained recognition of abnormal behaviors.
Proceedings of the 2015 IEEE International Conference on Pervasive Computing and Communication Workshops, 2015


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