Lloyd Hughes

About Lloyd Hughes

Lloyd Hughes, With an exceptional h-index of 13 and a recent h-index of 13 (since 2020), a distinguished researcher at Technische Universität München, specializes in the field of Deep Learning, Remote Sensing, Signal Processing.

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

Mapping drivers of tropical forest loss with satellite image time series and machine learning

On the selection and effectiveness of pseudo-absences for species distribution modeling with deep learning

Text as a richer source of supervision in semantic segmentation tasks

Sensor-agnostic Deep Learning of Coastal Ocean Chlorophyll-a

Exploring neural networks and their potential for species distribution modeling

An Unsupervised Method for the Detection of and Tracking of Targets in Spotlight Mode SAR Images

RepreSent: Non-supervised Representation Learning for Sentinels

Semi-Supervised Deep Learning Representations in Earth Observation Based Forest Management

Lloyd Hughes Information

University

Position

___

Citations(all)

1137

Citations(since 2020)

1118

Cited By

279

hIndex(all)

13

hIndex(since 2020)

13

i10Index(all)

14

i10Index(since 2020)

14

Email

University Profile Page

Google Scholar

Lloyd Hughes Skills & Research Interests

Deep Learning

Remote Sensing

Signal Processing

Top articles of Lloyd Hughes

Title

Journal

Author(s)

Publication Date

Mapping drivers of tropical forest loss with satellite image time series and machine learning

Environmental Research Letters

Jan Pisl

Marc Rußwurm

Lloyd Hughes

Gaston Lenczner

Linda See

...

2024/4/29

On the selection and effectiveness of pseudo-absences for species distribution modeling with deep learning

arXiv preprint arXiv:2401.02989

Robin Zbinden

Nina van Tiel

Benjamin Kellenberger

Lloyd Hughes

Devis Tuia

2024/1/3

Text as a richer source of supervision in semantic segmentation tasks

Valerie Zermatten

Javiera Castillo Navarro

Lloyd Hughes

Tobias Kellenberger

Devis Tuia

2023/7/16

Sensor-agnostic Deep Learning of Coastal Ocean Chlorophyll-a

Lloyd Hughes

Devis Tuia

Marie Smith

Lisl Lain

2023/9/1

Exploring neural networks and their potential for species distribution modeling

Robin Zbinden

Nina Marion Aurélia Van Tiel

Benjamin Alexander Kellenberger

Lloyd Hughes

Devis Tuia

2023/4/1

An Unsupervised Method for the Detection of and Tracking of Targets in Spotlight Mode SAR Images

Shaunak De

Kat Jensen

Victor Cazcarra-Bes

Nestor Yague

Davide Castelletti

...

2023/7/16

RepreSent: Non-supervised Representation Learning for Sentinels

Corneliu Octavian Dumitru

Ridvan Salih Kuzu

Lloyd Hughes

Marc Russwurm

Devis Tuia

...

2023

Semi-Supervised Deep Learning Representations in Earth Observation Based Forest Management

Oleg Antropov

Matthieu Molinier

Rıdvan Salih Kuzu

Lloyd Hughes

Marc Rußwurm

...

2023/7/16

Classification of Tropical Deforestation Drivers with Machine Learning and Satellite Image Time Series

Jan Pisl

Lloyd Haydn Hughes

Marc Rußwurm

Devis Tuia

2023/7/16

Detection of settlements in tanzania and mozambique by many regional few-shot models

Marc Rußwurm

Lloyd Haydn Hughes

Giorgio Pasquali

Corneliu Octavian Dumitru

Devis Tuia

2023/7/16

Flood Monitoring with X-Band and C-Band SAR: A Case Study of the 2021 British Columbia Floods

Kat Jensen

Shaunak De

Lloyd Hughes

Ganesh Yalla

2022/7/17

Single collect flood mapping from vhr x-band data supervised solely by ancillary data

Shaunak De

Kat Jensen

Lloyd Hughes

David Ruiz

Davide Castelletti

...

2022/7/17

Fully unsupervised bi-temporal change detection framework for vhr sar

Shaunak De

Lloyd Hughes

Davide Castelletti

Ganesh Yalla

2021/7/11

Comparative evaluation of deep learning-based SAR-optical image matching approaches

Lloyd Haydn Hughes

Michael Schmitt

2021/7/11

Improved Image Aggregation for Large-Scale Cloud-Free Image Creation

David Nagy

Zhenya Warshavsky

Lloyd Haydn Hughes

2021/7/11

Exploiting Aerial Imagery for Supervised Learning of SAR Despeckling Neural Networks

Lloyd Hughes

Shaunak De

Davide Castelletti

Ganesh Yalla

2021/7/11

So2Sat LCZ42: A benchmark data set for the classification of global local climate zones [Software and Data Sets]

IEEE Geoscience and Remote Sensing Magazine

Xiao Xiang Zhu

Jingliang Hu

Chunping Qiu

Yilei Shi

Jian Kang

...

2020/2/26

Deep learning for matching high-resolution SAR and optical imagery

Lloyd Haydn Hughes

2020

Multitask learning for human settlement extent regression and local climate zone classification

IEEE Geoscience and Remote Sensing Letters

Chunping Qiu

Lukas Liebel

Lloyd Haydn Hughes

Michael Schmitt

Marco Körner

...

2020/11/24

A deep learning framework for matching of SAR and optical imagery

ISPRS Journal of Photogrammetry and Remote Sensing

Lloyd Haydn Hughes

Diego Marcos

Sylvain Lobry

Devis Tuia

Michael Schmitt

2020/11/1

See List of Professors in Lloyd Hughes University(Technische Universität München)