Davide Dalle Pezze

Orcid: 0000-0002-4741-1021

According to our database1, Davide Dalle Pezze authored at least 15 papers between 2022 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Tiny Robotics Dataset and Benchmark for Continual Object Detection.
CoRR, 2024

Replay Consolidation with Label Propagation for Continual Object Detection.
CoRR, 2024

Latent Distillation for Continual Object Detection at the Edge.
CoRR, 2024

Fairness Evolution in Continual Learning for Medical Imaging.
CoRR, 2024

Multi-Label Continual Learning for the Medical Domain: A Novel Benchmark.
CoRR, 2024

Bayesian Deep Learning for Remaining Useful Life Estimation via Stein Variational Gradient Descent.
CoRR, 2024

An empirical evaluation of tinyML architectures for Class-Incremental Continual Learning.
Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2024

Unveiling the Anomalies in an Ever-Changing World: A Benchmark for Pixel-Level Anomaly Detection in Continual Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
AcME - Accelerated model-agnostic explanations: Fast whitening of the machine-learning black box.
Expert Syst. Appl., 2023

A multi-label Continual Learning framework to scale deep learning approaches for packaging equipment monitoring.
Eng. Appl. Artif. Intell., 2023

Predictive Maintenance in the Industry: A Comparative Study on Deep Learning-based Remaining Useful Life Estimation.
Proceedings of the 21st IEEE International Conference on Industrial Informatics, 2023

VIR2EM: VIrtualization and Remotization for Resilient and Efficient Manufacturing: Project-Dissemination Paper.
Proceedings of the Forum on Specification & Design Languages, 2023

2022
Alarm Logs in Packaging Industry (ALPI).
Dataset, May, 2022

FORMULA: A Deep Learning Approach for Rare Alarms Predictions in Industrial Equipment.
IEEE Trans Autom. Sci. Eng., 2022

Continual Learning Approaches for Anomaly Detection.
CoRR, 2022


  Loading...