Federico Zocco

Orcid: 0000-0002-6631-7081

According to our database1, Federico Zocco authored at least 19 papers between 2017 and 2024.

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

Timeline

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Links

On csauthors.net:

Bibliography

2024
Control of Multiple AUV Systems With Input Saturations Using Distributed Fixed-Time Consensus Fuzzy Control.
IEEE Trans. Fuzzy Syst., May, 2024

Synchronized Object Detection for Autonomous Sorting, Mapping, and Quantification of Medical Materials.
CoRR, 2024

Towards a Thermodynamical Deep-Learning-Vision-Based Flexible Robotic Cell for Circular Healthcare.
CoRR, 2024

A Unification Between Deep-Learning Vision, Compartmental Dynamical Thermodynamics, and Robotic Manipulation for a Circular Economy.
IEEE Access, 2024

2023
Towards More Efficient EfficientDets and Real-Time Marine Debris Detection.
IEEE Robotics Autom. Lett., April, 2023

Lazy FSCA for unsupervised variable selection.
Eng. Appl. Artif. Intell., 2023

Visual Material Characteristics Learning for Circular Healthcare.
CoRR, 2023

Distributed Fixed-Time Consensus Control for Multiple AUV Systems with Input Saturations.
CoRR, 2023

Digital Twins for Marine Operations: A Brief Review on Their Implementation.
CoRR, 2023

2022
Recovery of linear components: Reduced complexity autoencoder designs.
Eng. Appl. Artif. Intell., 2022

Circularity of Thermodynamical Material Networks: Indicators, Examples and Algorithms.
CoRR, 2022

Towards More Efficient EfficientDets and Low-Light Real-Time Marine Debris Detection.
CoRR, 2022

2021
Thermodynamical Material Networks for Modeling, Planning and Control of Circular Material Flows.
CoRR, 2021

Greedy Search Algorithms for Unsupervised Variable Selection: A Comparative Study.
CoRR, 2021

Material Measurement Units: Foundations Through a Survey.
CoRR, 2021

2020
Induced Start Dynamic Sampling for Wafer Metrology Optimization.
IEEE Trans Autom. Sci. Eng., 2020

An Adaptive Memory Multi-Batch L-BFGS Algorithm for Neural Network Training.
CoRR, 2020

2019
What are the Most Informative Data for Virtual Metrology? A use case on Multi-Stage Processes Fault Prediction.
Proceedings of the 15th IEEE International Conference on Automation Science and Engineering, 2019

2017
Mean Squared Error vs. Frame Potential for Unsupervised Variable Selection.
Proceedings of the Intelligent Computing, Networked Control, and Their Engineering Applications, 2017


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