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Jiayu Sun - IEEE Xplore Author Profile

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Author details

Jiayu Sun

Publications

6

Citations

120

Publications by Year

20202024

Co-Authors:

Guang FengGerhard HanckeZhiwei HuRynson LauHuchuan Lu

Show All Co-Authors (11)

Jiayu Sun

Affiliation

School of Information and Communication Engineering

Dalian University of Technology

Dalian, China

Publication Topics

Affinity Matrix,
Learnable Parameters,
Linguistic Context,
Linguistic Features,
Multimodal Features,
Semantic Segmentation,
Visual Features,
Attention Mechanism,
Attention Module,
Convolutional Neural Network,
Feature Maps,
Image Regions

Biography

Jiayu Sun received the BE degree in biomedical engineering from Northeastern University, Shenyang, China and the ME degree in electrical engineering from the University of Queensland, Brisbane, Australia, in 2016 and 2018 respectively. She is currently working toward the PhD degree in the Dalian University of Technology, Dalian, China. Her research interests include computer vision and machine learning.(Based on document published on 11 November 2022).

Publications

6

Citations

120

Publications by Year

20202024

Co-Authors:

Guang Feng
Gerhard Hancke
Zhiwei Hu
Rynson Lau
Huchuan Lu

Show All Co-Authors (11)

Author's Published Works

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Showing 1-13 of 13 results

Conferences (7)

Journals (6)

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Stefania Carapezzi(12)
Aida Todri-Sanial(7)
Corentin Delacour(6)
Elena Gnani(5)
Antonio Gnudi(5)
University of Bologna (ARCES - DEI), Bologna, Italy(3)
Microelectronics Department, LIRMM, Univ. of Montpellier, CNRS, Montpellier, France(2)
Microelectronics Department, LIRMM, University of Montpellier, CNRS, Montpellier, France(1)
Microelectronics Department LIRMM, Univ. of Montpellier, CNRS, Montpellier, France(1)
Laboratoire d’informatique, de robotique et de microélectronique de Montpellier, Centre national de la recherche Scientifique, University of Montpellier, Montpellier, France(1)
IEEE Transactions on Electron Devices(2)
IEEE Transactions on Neural Networks and Learning Systems(2)
2016 46th European Solid-State Device Research Conference (ESSDERC)(1)
2017 IEEE International Electron Devices Meeting (IEDM)(1)
2018 48th European Solid-State Device Research Conference (ESSDERC)(1)
IEEE(13)
Cracow, Poland(1)
Dresden, Germany(1)
Lausanne, Switzerland(1)
San Francisco, CA, USA(1)
Tampa, FL, USA(1)
Hopfield Neural Network(5)
Network Oscillations(5)
Neural Network(5)
Pattern Recognition(5)
Circuit Simulation(4)

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Energy-Performance Assessment of Oscillatory Neural Networks Based on VO2 Devices for Future Edge AI Computing

Corentin Delacour;Stefania Carapezzi;Madeleine Abernot;Aida Todri-Sanial

IEEE Transactions on Neural Networks and Learning Systems

Year: 2024 | Volume: 35, Issue: 7 | Journal Article |

Cited by: Papers (15)

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Oscillatory neural network (ONN) is an emerging neuromorphic architecture composed of oscillators that implement neurons and are coupled by synapses. ONNs exhibit rich dynamics and associative properties, which can be used to solve problems in the analog domain according to the paradigm let physics compute. For example, compact oscillators made of VO2 material are good candidates for building low-...Show More

Energy-Performance Assessment of Oscillatory Neural Networks Based on VO2 Devices for Future Edge AI Computing

Corentin Delacour;Stefania Carapezzi;Madeleine Abernot;Aida Todri-Sanial

IEEE Transactions on Neural Networks and Learning Systems

Year: 2024 | Volume: 35, Issue: 7 | Journal Article |

Simulation Toolchain for Neuromorphic Oscillatory Neural Networks Based on Beyond-CMOS Vanadium Dioxide Devices

Stefania Carapezzi;Corentin Delacour;Aida Todri-Sanial

2022 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)

Year: 2022 | Conference Paper |

Cited by: Papers (1)

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In this work, we illustrate a simulation toolchain using technology computer-aided design (TCAD) software to simulate neuro-mimicking Oscillatory Neural Networks (ONNs) based on Beyond CMOS Vanadium Dioxide (VO2) oscillators. We use a dedicated TCAD approach to simulate thermal-induced resistive switching in VO2. We perform TCAD and TCAD -SPICE mixed-mode simulations to simulate all the key elemen...Show More

Simulation Toolchain for Neuromorphic Oscillatory Neural Networks Based on Beyond-CMOS Vanadium Dioxide Devices

Stefania Carapezzi;Corentin Delacour;Aida Todri-Sanial

2022 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)

Year: 2022 | Conference Paper |

How Frequency Injection Locking Can Train Oscillatory Neural Networks to Compute in Phase

Aida Todri-Sanial;Stefania Carapezzi;Corentin Delacour;Madeleine Abernot;Thierry Gil;Elisabetta Corti;Siegfried F. Karg;Juan Nüñez;Manuel Jiménèz;María J. Avedillo;Bernabé Linares-Barranco

IEEE Transactions on Neural Networks and Learning Systems

Year: 2022 | Volume: 33, Issue: 5 | Journal Article |

Cited by: Papers (25)

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Brain-inspired computing employs devices and architectures that emulate biological functions for more adaptive and energy-efficient systems. Oscillatory neural networks (ONNs) are an alternative approach in emulating biological functions of the human brain and are suitable for solving large and complex associative problems. In this work, we investigate the dynamics of coupled oscillators to implem...Show More

How Frequency Injection Locking Can Train Oscillatory Neural Networks to Compute in Phase

Aida Todri-Sanial;Stefania Carapezzi;Corentin Delacour;Madeleine Abernot;Thierry Gil;Elisabetta Corti;Siegfried F. Karg;Juan Nüñez;Manuel Jiménèz;María J. Avedillo;Bernabé Linares-Barranco

IEEE Transactions on Neural Networks and Learning Systems

Year: 2022 | Volume: 33, Issue: 5 | Journal Article |

Advanced Design Methods From Materials and Devices to Circuits for Brain-Inspired Oscillatory Neural Networks for Edge Computing

Stefania Carapezzi;Gabriele Boschetto;Corentin Delacour;Elisabetta Corti;Andrew Plews;Ahmed Nejim;Siegfried Karg;Aida Todri-Sanial

IEEE Journal on Emerging and Selected Topics in Circuits and Systems

Year: 2021 | Volume: 11, Issue: 4 | Journal Article |

Cited by: Papers (12)

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In this paper, we assess an innovative concept of emulating biological neurons with oscillators to implement an oscillatory neural network (ONN) with beyond-CMOS devices based on vanadium dioxide (VO2). ONNs can be of interest as an ultra-low-power neuromorphic architecture capable of performing associative memory tasks, such as pattern recognition in IoT edge devices. To explore the benefits and ...Show More

Advanced Design Methods From Materials and Devices to Circuits for Brain-Inspired Oscillatory Neural Networks for Edge Computing

Stefania Carapezzi;Gabriele Boschetto;Corentin Delacour;Elisabetta Corti;Andrew Plews;Ahmed Nejim;Siegfried Karg;Aida Todri-Sanial

IEEE Journal on Emerging and Selected Topics in Circuits and Systems

Year: 2021 | Volume: 11, Issue: 4 | Journal Article |

Graphene and Carbon Nanotubes for Electronics Nanopackaging

Gabriele Boschetto;Stefania Carapezzi;Aida Todri-Sanial

IEEE Open Journal of Nanotechnology

Year: 2021 | Volume: 2 | Journal Article |

Cited by: Papers (10)

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In recent years, the aggressive downscaling of electronic components has led to highly dense and power-hungry devices. With Moore’s law expected to soon reach its physical limit, there is a pressing need to significantly improve the efficiency and performance not only of nanodevices, but also of the embedding environment in which such nanodevices are integrated. In this context, key for improving ...Show More

Graphene and Carbon Nanotubes for Electronics Nanopackaging

Gabriele Boschetto;Stefania Carapezzi;Aida Todri-Sanial

IEEE Open Journal of Nanotechnology

Year: 2021 | Volume: 2 | Journal Article |

Oscillatory Neural Networks for Edge AI Computing

Corentin Delacour;Stefania Carapezzi;Madeleine Abernot;Gabriele Boschetto;Nadine Azemard;Jeremie Salles;Thierry Gil;Aida Todri-Sanial

2021 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)

Year: 2021 | Conference Paper |

Cited by: Papers (11)

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In this paper, we showcase the innovative concept of implementing Oscillatory Neural Networks (ONNs) for neuromorphic computing with beyond-CMOS devices based on vanadium dioxide to mimic neurons and resistors to emulate synapses. We explore ONN technology potentials from device to analog circuit-level simulations. We report that ONN behaves like an associative memory and can implement energy-base...Show More

Oscillatory Neural Networks for Edge AI Computing

Corentin Delacour;Stefania Carapezzi;Madeleine Abernot;Gabriele Boschetto;Nadine Azemard;Jeremie Salles;Thierry Gil;Aida Todri-Sanial

2021 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)

Year: 2021 | Conference Paper |

Multi-Scale Modeling and Simulation Flow for Oscillatory Neural Networks for Edge Computing

Stefania Carapezzi;Corentin Delacour;Gabriele Boschetto;Elisabetta Corti;Madeleine Abernot;Ahmed Nejim;Thierry Gil;Siegfried Karg;Aida Todri-Sanial

2021 19th IEEE International New Circuits and Systems Conference (NEWCAS)

Year: 2021 | Conference Paper |

Cited by: Papers (6)

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An oscillatory neural network (ONN) is a neuromorphic computing paradigm based on encoding of information into the phases of oscillators. In this paper we present an ONN whose elemental unit, the "neuron", is implemented through a beyond-CMOS device based on vanadium dioxide (VO2). Such ONN technology provides ultra-low power solutions for performing pattern recognition tasks, and it is ideally su...Show More

Multi-Scale Modeling and Simulation Flow for Oscillatory Neural Networks for Edge Computing

Stefania Carapezzi;Corentin Delacour;Gabriele Boschetto;Elisabetta Corti;Madeleine Abernot;Ahmed Nejim;Thierry Gil;Siegfried Karg;Aida Todri-Sanial

2021 19th IEEE International New Circuits and Systems Conference (NEWCAS)

Year: 2021 | Conference Paper |

TCAD Simulation Framework of Gas Desorption in CNT FET NO2 Sensors

Stefania Carapezzi;Susanna Reggiani;Elena Gnani;Antonio Gnudi

IEEE Transactions on Electron Devices

Year: 2020 | Volume: 67, Issue: 11 | Journal Article |

Cited by: Papers (3)

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A technology computer-aided design (TCAD) simulation framework of gas desorption induced by self-heating in carbon nanotube (CNT) field effect transistor (FET) gas sensors is presented. Its key feature is the use of temperature profiles extracted from electrothermal simulations to determine the change of the effective gas-induced doping concentration during the gas desorption phase. The approach a...Show More

TCAD Simulation Framework of Gas Desorption in CNT FET NO2 Sensors

Stefania Carapezzi;Susanna Reggiani;Elena Gnani;Antonio Gnudi

IEEE Transactions on Electron Devices

Year: 2020 | Volume: 67, Issue: 11 | Journal Article |

On the electron mobility of strained InGaAs channel MOSFETs

Stefania Carapezzi;Susanna Reggiani;Elena Gnani;Antonio Gnudi

ESSDERC 2019 - 49th European Solid-State Device Research Conference (ESSDERC)

Year: 2019 | Conference Paper |

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A discussion over the microscopic electron mobility of strained InGaAs channels of metal-oxide-semiconductor field-effect transistors (MOSFETs) is presented. The theoretical model is validated against experimental results of strained InGaAs-on-Insulator (InGaAs-OI) MOSFETs. It accurately reproduces effective and Hall mobilities vs. charge density curves, once the calibration of interface trap dens...Show More

On the electron mobility of strained InGaAs channel MOSFETs

Stefania Carapezzi;Susanna Reggiani;Elena Gnani;Antonio Gnudi

ESSDERC 2019 - 49th European Solid-State Device Research Conference (ESSDERC)

Year: 2019 | Conference Paper |

3D TCAD modeling of NO2CNT FET sensors

Stefania Carapezzi;Sebastian Eberle;Susanna Reggiani;Elena Gnani;Cosmin Roman;Christofer Hierold;Antonio Gnudi

2018 48th European Solid-State Device Research Conference (ESSDERC)

Year: 2018 | Conference Paper |

Cited by: Papers (2)

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A new approach for TCAD modeling of CNT FET gas sensors is presented, whose key feature is the use of an effective Gaussian DOS to mimic the 1D CNT DOS. The TCAD procedure has been applied to the simulation of a suspended CNT FET for NO2 sensing. Our results indicate that the model is able to provide I- V characteristics in excellent agreement with the experimental data, both before and after gas ...Show More

3D TCAD modeling of NO2CNT FET sensors

Stefania Carapezzi;Sebastian Eberle;Susanna Reggiani;Elena Gnani;Cosmin Roman;Christofer Hierold;Antonio Gnudi

2018 48th European Solid-State Device Research Conference (ESSDERC)

Year: 2018 | Conference Paper |

Modelling nanoscale n-MOSFETs with III-V compound semiconductor channels: From advanced models for band structures, electrostatics and transport to TCAD

L. Selmi;E. Caruso;S. Carapezzi;M. Visciarelli;E. Gnani;N. Zagni;P. Pavan;P. Palestri;D. Esseni;A. Gnudi;S. Reggiani;F. M. Puglisi;G. Verzellesi

2017 IEEE International Electron Devices Meeting (IEDM)

Year: 2017 | Conference Paper |

Cited by: Papers (8)

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We review a few state of the art solutions and recent developments to model short channel III-V compound semiconductor n-MOSFETs based on full quantum transport, semiclassical multi-valley / multi-subband transport and TCAD models. The pros and cons of each, and the insights they can deliver, are illustrated with examples from recent technology developments and literature. Areas where improvements...Show More

Modelling nanoscale n-MOSFETs with III-V compound semiconductor channels: From advanced models for band structures, electrostatics and transport to TCAD

L. Selmi;E. Caruso;S. Carapezzi;M. Visciarelli;E. Gnani;N. Zagni;P. Pavan;P. Palestri;D. Esseni;A. Gnudi;S. Reggiani;F. M. Puglisi;G. Verzellesi

2017 IEEE International Electron Devices Meeting (IEDM)

Year: 2017 | Conference Paper |

TCAD Mobility Model of III-V Short-Channel Double-Gate FETs Including Ballistic Corrections

Stefania Carapezzi;Enrico Caruso;Antonio Gnudi;Pierpaolo Palestri;Susanna Reggiani;Elena Gnani

IEEE Transactions on Electron Devices

Year: 2017 | Volume: 64, Issue: 12 | Journal Article |

Cited by: Papers (6)

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A TCAD-oriented mobility model, whose main features are: 1) inclusion of ballistic effects in the linear region and 2) smooth transition between the linear and saturation regions, is presented. It is applied to short-channel double-gate thin-body InGaAs MOSFETs. The bases of the model are the concept of ballistic mobility and Matthiessen's rule in the linear regime, and the saturation velocity wit...Show More

TCAD Mobility Model of III-V Short-Channel Double-Gate FETs Including Ballistic Corrections

Stefania Carapezzi;Enrico Caruso;Antonio Gnudi;Pierpaolo Palestri;Susanna Reggiani;Elena Gnani

IEEE Transactions on Electron Devices

Year: 2017 | Volume: 64, Issue: 12 | Journal Article |

TCAD low-field mobility model for InGaAs UTB MOSFETs including quasi-ballistic corrections

Stefania Carapezzi;Enrico Caruso;Antonio Gnudi;Susanna Reggiani;Elena Gnani

2016 46th European Solid-State Device Research Conference (ESSDERC)

Year: 2016 | Conference Paper |

Cited by: Papers (3)

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A new approach for including quasi-ballistic effects into TCAD drift diffusion simulations of short-channel III–V MOSFETs at low longitudinal fields is presented. The model is based on the concept of ballistic mobility through a modified Matthiessen rule. It has been applied to double-gate thin-body InGaAs MOSFETs and benchmarked against multi-subband Monte Carlo simulations. Our results indicate ...Show More

TCAD low-field mobility model for InGaAs UTB MOSFETs including quasi-ballistic corrections

Stefania Carapezzi;Enrico Caruso;Antonio Gnudi;Susanna Reggiani;Elena Gnani

2016 46th European Solid-State Device Research Conference (ESSDERC)

Year: 2016 | Conference Paper |

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