Vito Paolo Pastore

Orcid: 0000-0002-5827-5571

According to our database1, Vito Paolo Pastore authored at least 27 papers between 2015 and 2024.

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Bibliography

2024
Computer vision and deep learning meet plankton: Milestones and future directions.
Image Vis. Comput., 2024

Top-tuning: A study on transfer learning for an efficient alternative to fine tuning for image classification with fast kernel methods.
Image Vis. Comput., 2024

Say My Name: a Model's Bias Discovery Framework.
CoRR, 2024

Self-supervised pre-training with diffusion model for few-shot landmark detection in x-ray images.
CoRR, 2024

Looking at Model Debiasing through the Lens of Anomaly Detection.
CoRR, 2024

Ensembles of Deep Neural Networks for the Automatic Detection of Building Facade Defects From Images.
IEEE Access, 2024

Is In-Domain Data Beneficial in Transfer Learning for Landmarks Detection in X-Ray Images?
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

2023
Efficient unsupervised learning of biological images with compressed deep features.
Image Vis. Comput., September, 2023

A Control-Oriented Highway Traffic Model with Multiple Clusters of CAVs.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

Incorporating Diagnostic Prior with Segmentation: A Deep Learning Pipeline for the Automatic Classification of Autoimmune Bullous Skin Diseases.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Food Image Classification: The Benefit of In-Domain Transfer Learning.
Proceedings of the Image Analysis and Processing - ICIAP 2023, 2023

An Unsupervised Learning Approach to Resolve Phenotype to Genotype Mapping in Budding Yeasts Vacuoles.
Proceedings of the Image Analysis and Processing - ICIAP 2023, 2023

GCK-Maps: A Scene Unbiased Representation for Efficient Human Action Recognition.
Proceedings of the Image Analysis and Processing - ICIAP 2023, 2023

AGAMAS: A New Agent-Oriented Traffic Simulation Framework for SUMO.
Proceedings of the Multi-Agent Systems - 20th European Conference, 2023

An efficient deep learning approach to identify dynamics in in vitro neural networks.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

2022
Fine-tuning or top-tuning? Transfer learning with pretrained features and fast kernel methods.
CoRR, 2022

A markerless pipeline to analyze spontaneous movements of preterm infants.
Comput. Methods Programs Biomed., 2022

Efficient Unsupervised Learning for Plankton Images.
Proceedings of the 26th International Conference on Pattern Recognition, 2022

An Anomaly Detection Approach for Plankton Species Discovery.
Proceedings of the Image Analysis and Processing - ICIAP 2022, 2022

2018
Development of statistical and computational methods to estimate functional connectivity and topology in large-scale neuronal assemblies.
PhD thesis, 2018

Identification of excitatory-inhibitory links and network topology in large-scale neuronal assemblies from multi-electrode recordings.
PLoS Comput. Biol., 2018

SpiCoDyn: A Toolbox for the Analysis of Neuronal Network Dynamics and Connectivity from Multi-Site Spike Signal Recordings.
Neuroinformatics, 2018

2017
Corrigendum: ToolConnect: A Functional Connectivity Toolbox for In vitro Networks.
Frontiers Neuroinformatics, 2017

A toolbox for dynamic and connectivity analysis of neuronal spike trains data.
Proceedings of the 8th International IEEE/EMBS Conference on Neural Engineering, 2017

2016
ToolConnect: A Functional Connectivity Toolbox for In vitro Networks.
Frontiers Neuroinformatics, 2016

2015
Functional connectivity in cultured cortical networks during development: Comparison between correlation and information theory-based algorithms.
Proceedings of the 7th International IEEE/EMBS Conference on Neural Engineering, 2015

A new connectivity toolbox to infer topological features of in-vitro neural networks.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015


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