Ilayda Yaman

About Ilayda Yaman

Ilayda Yaman, With an exceptional h-index of 2 and a recent h-index of 2 (since 2020), a distinguished researcher at Lunds Universitet, specializes in the field of Electronics Engineering.

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

The LuViRA dataset: measurement description

High-precision machine-learning based indoor localization with massive MIMO system

Deep-learning based high-precision localization with massive MIMO

Indoor Localization Using Radio, Vision and Audio Sensors: Real-Life Data Validation and Discussion

FLoPAD-GRU: A Flexible, Low Power, Accelerated DSP for Gated Recurrent Unit Neural Network

A Hardware Accelerated Low Power DSP for Recurrent Neural Networks

Ilayda Yaman Information

University

Position

___

Citations(all)

12

Citations(since 2020)

12

Cited By

1

hIndex(all)

2

hIndex(since 2020)

2

i10Index(all)

0

i10Index(since 2020)

0

Email

University Profile Page

Google Scholar

Ilayda Yaman Skills & Research Interests

Electronics Engineering

Top articles of Ilayda Yaman

The LuViRA dataset: measurement description

arXiv preprint arXiv:2302.05309

2023/2/10

High-precision machine-learning based indoor localization with massive MIMO system

2023/5/28

Deep-learning based high-precision localization with massive MIMO

IEEE Transactions on Machine Learning in Communications and Networking

2023/11/28

Indoor Localization Using Radio, Vision and Audio Sensors: Real-Life Data Validation and Discussion

arXiv preprint arXiv:2309.02961

2023/9/6

FLoPAD-GRU: A Flexible, Low Power, Accelerated DSP for Gated Recurrent Unit Neural Network

2021/8/23

Ilayda Yaman
Ilayda Yaman

H-Index: 1

Lucas Ferreira
Lucas Ferreira

H-Index: 1

A Hardware Accelerated Low Power DSP for Recurrent Neural Networks

2020

Ilayda Yaman
Ilayda Yaman

H-Index: 1

See List of Professors in Ilayda Yaman University(Lunds Universitet)