H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Engineering and Technology D-index 30 Citations 4,523 237 World Ranking 6791 National Ranking 251

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Algorithm

Aurelio Uncini mainly focuses on Algorithm, Artificial neural network, Artificial intelligence, Nonlinear system and Adaptive filter. Aurelio Uncini combines subjects such as Kernel method, Kernel, Spline, Mathematical optimization and Intersymbol interference with his study of Algorithm. His Artificial neural network study frequently draws connections between related disciplines such as Speech recognition.

The concepts of his Artificial intelligence study are interwoven with issues in Computational complexity theory, Machine learning, Theoretical computer science and Pattern recognition. His study looks at the relationship between Nonlinear system and fields such as Nonlinear adaptive filter, as well as how they intersect with chemical problems. His Adaptive filter research is multidisciplinary, relying on both Human–computer interaction and Language of mathematics.

His most cited work include:

  • Group sparse regularization for deep neural networks (232 citations)
  • On-line learning algorithms for locally recurrent neural networks (148 citations)
  • Applications of simulated annealing for the design of special digital filters (137 citations)

What are the main themes of his work throughout his whole career to date?

Aurelio Uncini mostly deals with Algorithm, Artificial neural network, Artificial intelligence, Nonlinear system and Adaptive filter. His Algorithm study incorporates themes from Speech recognition, Mathematical optimization, Blind signal separation and Signal processing. His Artificial intelligence research incorporates elements of Machine learning, Computer vision and Pattern recognition.

His Nonlinear system study combines topics in areas such as Nonlinear system identification, Echo, Mutual information, Spline and Nonlinear filter. The study incorporates disciplines such as Transfer function and Adaptive system in addition to Spline. Aurelio Uncini works mostly in the field of Adaptive filter, limiting it down to concerns involving Filter design and, occasionally, Digital filter.

He most often published in these fields:

  • Algorithm (42.66%)
  • Artificial neural network (32.08%)
  • Artificial intelligence (31.40%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (31.40%)
  • Artificial neural network (32.08%)
  • Algorithm (42.66%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Artificial intelligence, Artificial neural network, Algorithm, Machine learning and Nonlinear system. His Artificial intelligence study integrates concerns from other disciplines, such as Quaternion and Pattern recognition. When carried out as part of a general Artificial neural network research project, his work on Overfitting is frequently linked to work in Memory footprint, therefore connecting diverse disciplines of study.

Many of his research projects under Algorithm are closely connected to Domain with Domain, tying the diverse disciplines of science together. His Machine learning research is multidisciplinary, incorporating elements of Audio signal processing, Embedding and Ambisonics. He interconnects Low complexity, Control parameters and Excess mean square error in the investigation of issues within Nonlinear system.

Between 2017 and 2021, his most popular works were:

  • Kafnets: Kernel-based non-parametric activation functions for neural networks. (40 citations)
  • Deep Region of Interest and Feature Extraction Models for Palmprint Verification Using Convolutional Neural Networks Transfer Learning (32 citations)
  • Complex-Valued Neural Networks With Nonparametric Activation Functions (21 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Statistics

Aurelio Uncini mainly focuses on Artificial intelligence, Artificial neural network, Machine learning, Inference and Algorithm. His studies link Field with Artificial intelligence. Aurelio Uncini undertakes multidisciplinary studies into Artificial neural network and Memory footprint in his work.

Aurelio Uncini combines subjects such as Embedding, Sound and Identification with his study of Machine learning. His research integrates issues of Regularization, Computation, Outlier and Bayesian inference in his study of Inference. Aurelio Uncini integrates Algorithm and Domain in his research.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Group sparse regularization for deep neural networks

Simone Scardapane;Danilo Comminiello;Amir Hussain;Aurelio Uncini.
Neurocomputing (2017)

288 Citations

On-line learning algorithms for locally recurrent neural networks

P. Campolucci;A. Uncini;F. Piazza;B.D. Rao.
IEEE Transactions on Neural Networks (1999)

210 Citations

Applications of simulated annealing for the design of special digital filters

N. Benvenuto;M. Marchesi;A. Uncini.
IEEE Transactions on Signal Processing (1992)

208 Citations

Learning and approximation capabilities of adaptive spline activation function neutral networks

Lorenzo Vecci;Francesco Piazza;Aurelio Uncini.
Neural Networks (1998)

175 Citations

Fast neural networks without multipliers

M. Marchesi;G. Orlandi;F. Piazza;A. Uncini.
IEEE Transactions on Neural Networks (1993)

169 Citations

Online Sequential Extreme Learning Machine With Kernels

Simone Scardapane;Danilo Comminiello;Michele Scarpiniti;Aurelio Uncini.
IEEE Transactions on Neural Networks (2015)

137 Citations

Multilayer feedforward networks with adaptive spline activation function

S. Guarnieri;F. Piazza;A. Uncini.
IEEE Transactions on Neural Networks (1999)

136 Citations

Nonlinear spline adaptive filtering

Michele Scarpiniti;Danilo Comminiello;Raffaele Parisi;Aurelio Uncini.
Signal Processing (2013)

127 Citations

Distributed learning for Random Vector Functional-Link networks

Simone Scardapane;Dianhui Wang;Massimo Panella;Aurelio Uncini.
Information Sciences (2015)

125 Citations

Functional Link Adaptive Filters for Nonlinear Acoustic Echo Cancellation

D. Comminiello;M. Scarpiniti;L. A. Azpicueta-Ruiz;J. Arenas-Garcia.
IEEE Transactions on Audio, Speech, and Language Processing (2013)

122 Citations

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