Radu Dogaru

About Radu Dogaru

Radu Dogaru, With an exceptional h-index of 18 and a recent h-index of 7 (since 2020), a distinguished researcher at Universitatea Politehnica din Bucuresti, specializes in the field of Computational Intelligence, Complex Nonlinear Networks and Dynamics, Reconfigurable and High Performance Computing, Nonlinear.

His recent articles reflect a diverse array of research interests and contributions to the field:

XNL-CNN: An improved version of the NL-CNN model, for running with TPU accelerators and large image datasets

V-CNN: A Versatile Light CNN Structure For Image Recognition On Resources Constrained Platforms

A Comparison of Low Complexity CNN Models and Data Enhancement for Efficient Android Implementation of Leaves Recognition

The C-CNN model: Do we really need multiplicative synapses in convolutional neural networks?

State of the Art Recognition of Emotions from Speech, Using a Low Complexity Solution Based on Reaction-Diffusion Transform

LB-CNN: An Open Source Framework for Fast Training of Light Binary Convolutional Neural Networks using Chainer and Cupy

A Python Framework for Fast Modelling and Simulation of Cellular Nonlinear Networks and other Finite-difference Time-domain Systems

NL-CNN: A Resources-Constrained Deep Learning Model based on Nonlinear Convolution

Radu Dogaru Information

University

Position

Professor

Citations(all)

1594

Citations(since 2020)

260

Cited By

1454

hIndex(all)

18

hIndex(since 2020)

7

i10Index(all)

40

i10Index(since 2020)

6

Email

University Profile Page

Universitatea Politehnica din Bucuresti

Google Scholar

View Google Scholar Profile

Radu Dogaru Skills & Research Interests

Computational Intelligence

Complex Nonlinear Networks and Dynamics

Reconfigurable and High Performance Computing

Nonlinear

Top articles of Radu Dogaru

Title

Journal

Author(s)

Publication Date

XNL-CNN: An improved version of the NL-CNN model, for running with TPU accelerators and large image datasets

Radu Dogaru

Adrian-Dumitru Mirică

Ioana Dogaru

2023/10/26

V-CNN: A Versatile Light CNN Structure For Image Recognition On Resources Constrained Platforms

Radu Dogaru

Ioana Dogaru

2023/10/26

A Comparison of Low Complexity CNN Models and Data Enhancement for Efficient Android Implementation of Leaves Recognition

Alin-Gabriel Cococi

Radu Dogaru

2023/3/23

The C-CNN model: Do we really need multiplicative synapses in convolutional neural networks?

Radu Degaru

Adrian-Dumitru Mirică

Ioana Dogaru

2022/6/16

State of the Art Recognition of Emotions from Speech, Using a Low Complexity Solution Based on Reaction-Diffusion Transform

Radu Dogaru

Ioana Dogaru

2022/11/10

LB-CNN: An Open Source Framework for Fast Training of Light Binary Convolutional Neural Networks using Chainer and Cupy

arXiv preprint arXiv:2106.15350

Radu Dogaru

Ioana Dogaru

2021/6/25

A Python Framework for Fast Modelling and Simulation of Cellular Nonlinear Networks and other Finite-difference Time-domain Systems

Radu Dogaru

Ioana Dogaru

2021/5/26

NL-CNN: A Resources-Constrained Deep Learning Model based on Nonlinear Convolution

Radu Dogaru

Ioana Dogaru

2021/3/25

Disease detection on medical images using light-weight convolutional neural networks for resource constrained platforms

Alin-Gabriel Cococi

Daniel-Mihai Armanda

Iulian-Ionut Felea

Radu Dogaru

2020/11/5

Pneumonia detection on chest X-ray images using convolutional neural networks designed for resource constrained environments

Alin Cococi

Iulian Felea

Daniel Armanda

Radu Dogaru

2020/10/29

Fast training of light binary convolutional neural networks using chainer and cupy

Radu Dogaru

Ioana Dogaru

2020/6/25

Improving Light-weight Convolutional Neural Networks for Face Recognition Targeting Resource Constrained Platforms.

Iulian-Ionut Felea

Radu Dogaru

2020

RD-CNN: A compact and efficient convolutional neural net for sound classification

Radu Dogaru

Ioana Dogaru

2020/11/5

See List of Professors in Radu Dogaru University(Universitatea Politehnica din Bucuresti)