548 citations · 1.2k across the 31 of their papers we have counts for
32 papers
Physics-Informed Super-Resolution of Atmospheric Data
Chang Xu, Gencer Sumbul, Hugo Porta +3
In the context of global warming, extreme events have become more frequent and intense, making their trustworthy detection and forecasting more important than ever. Yet, atmospheri…
Prompting-MammAlps: Fine-Grained Text-to-Video Retrieval for Camera-Trap Data
Valentin Gabeff, Baptiste Maquignaz, Jennifer Shan +5
Automatically retrieving videos from large camera-trap datasets remains challenging. Text-to-Video retrieval (TVR) methods based on large video-language models (VLMs) have potentia…
A Geolocation-Aware Multimodal Approach for Ecological Prediction
Valerie Zermatten, Chiara Vanalli, Gencer Sumbul +2
While integrating multiple modalities has the potential to improve environmental monitoring, current approaches struggle to combine data sources with heterogeneous formats or conte…
SMARTIES: Spectrum-Aware Multi-Sensor Auto-Encoder for Remote Sensing Images
Gencer Sumbul, Chang Xu, Emanuele Dalsasso +1
From optical sensors to microwave radars, leveraging the complementary strengths of remote sensing (RS) sensors is crucial for achieving dense spatio-temporal monitoring of our pla…
Redundancy-Aware Pretraining of Vision-Language Foundation Models in Remote Sensing
Mathis Jürgen Adler, Leonard Hackel, Gencer Sumbul +1
The development of foundation models through pretraining of vision-language models (VLMs) has recently attracted great attention in remote sensing (RS). VLM pretraining aims to lea…
A Multi-Modal Federated Learning Framework for Remote Sensing Image Classification
Barış Büyüktaş, Gencer Sumbul, Begüm Demir
Federated learning (FL) enables the collaborative training of deep neural networks across decentralized data archives (i.e., clients) without sharing the local data of the clients.…
MaskSDM with Shapley values to improve flexibility, robustness, and explainability in species distribution modeling
Robin Zbinden, Nina van Tiel, Gencer Sumbul +3
Species Distribution Models (SDMs) play a vital role in biodiversity research, conservation planning, and ecological niche modeling by predicting species distributions based on env…
reBEN: Refined BigEarthNet Dataset for Remote Sensing Image Analysis
Kai Norman Clasen, Leonard Hackel, Tom Burgert +3
This paper presents refined BigEarthNet (reBEN) that is a large-scale, multi-modal remote sensing dataset constructed to support deep learning (DL) studies for remote sensing image…
Annotation Cost-Efficient Active Learning for Deep Metric Learning Driven Remote Sensing Image Retrieval
Genc Hoxha, Gencer Sumbul, Julia Henkel +2
Deep metric learning (DML) has shown to be effective for content-based image retrieval (CBIR) in remote sensing (RS). Most of DML methods for CBIR rely on a high number of annotate…
Exploring Masked Autoencoders for Sensor-Agnostic Image Retrieval in Remote Sensing
Jakob Hackstein, Gencer Sumbul, Kai Norman Clasen +1
Self-supervised learning through masked autoencoders (MAEs) has recently attracted great attention for remote sensing (RS) image representation learning, and thus embodies a signif…
Federated Learning Across Decentralized and Unshared Archives for Remote Sensing Image Classification
Barış Büyüktaş, Gencer Sumbul, Begüm Demir
Federated learning (FL) enables the collaboration of multiple deep learning models to learn from decentralized data archives (i.e., clients) without accessing data on clients. Alth…
Annotation Cost Efficient Active Learning for Content Based Image Retrieval
Julia Henkel, Genc Hoxha, Gencer Sumbul +2
Deep metric learning (DML) based methods have been found very effective for content-based image retrieval (CBIR) in remote sensing (RS). For accurately learning the model parameter…
Label Noise Robust Image Representation Learning based on Supervised Variational Autoencoders in Remote Sensing
Gencer Sumbul, Begüm Demir
Due to the publicly available thematic maps and crowd-sourced data, remote sensing (RS) image annotations can be gathered at zero cost for training deep neural networks (DNNs). How…
Learning Across Decentralized Multi-Modal Remote Sensing Archives with Federated Learning
Barış Büyüktaş, Gencer Sumbul, Begüm Demir
The development of federated learning (FL) methods, which aim to learn from distributed databases (i.e., clients) without accessing data on clients, has recently attracted great at…
Generative Reasoning Integrated Label Noise Robust Deep Image Representation Learning
Gencer Sumbul, Begüm Demir
The development of deep learning based image representation learning (IRL) methods has attracted great attention for various image understanding problems. Most of these methods req…
Deep Active Learning for Multi-Label Classification of Remote Sensing Images
Lars Möllenbrok, Gencer Sumbul, Begüm Demir
In this letter, we introduce deep active learning (AL) for multi-label classification (MLC) problems in remote sensing (RS). In particular, we investigate the effectiveness of seve…
A Novel Self-Supervised Cross-Modal Image Retrieval Method In Remote Sensing
Gencer Sumbul, Markus Müller, Begüm Demir
Due to the availability of multi-modal remote sensing (RS) image archives, one of the most important research topics is the development of cross-modal RS image retrieval (CM-RSIR)…
Deep Metric Learning-Based Semi-Supervised Regression With Alternate Learning
Adina Zell, Gencer Sumbul, Begüm Demir
This paper introduces a novel deep metric learning-based semi-supervised regression (DML-S2R) method for parameter estimation problems. The proposed DML-S2R method aims to mitigate…
A Novel Framework to Jointly Compress and Index Remote Sensing Images for Efficient Content-Based Retrieval
Gencer Sumbul, Jun Xiang, Nimisha Thekke Madam +1
Remote sensing (RS) images are usually stored in compressed format to reduce the storage size of the archives. Thus, existing content-based image retrieval (CBIR) systems in RS req…
BigEarthNet-MM: A Large Scale Multi-Modal Multi-Label Benchmark Archive for Remote Sensing Image Classification and Retrieval
Gencer Sumbul, Arne de Wall, Tristan Kreuziger +6
This paper presents the multi-modal BigEarthNet (BigEarthNet-MM) benchmark archive made up of 590,326 pairs of Sentinel-1 and Sentinel-2 image patches to support the deep learning…
A Novel Graph-Theoretic Deep Representation Learning Method for Multi-Label Remote Sensing Image Retrieval
Gencer Sumbul, Begüm Demir
This paper presents a novel graph-theoretic deep representation learning method in the framework of multi-label remote sensing (RS) image retrieval problems. The proposed method ai…
Informative and Representative Triplet Selection for Multilabel Remote Sensing Image Retrieval
Gencer Sumbul, Mahdyar Ravanbakhsh, Begüm Demir
Learning the similarity between remote sensing (RS) images forms the foundation for content-based RS image retrieval (CBIR). Recently, deep metric learning approaches that map the…
A Comparative Study of Deep Learning Loss Functions for Multi-Label Remote Sensing Image Classification
Hichame Yessou, Gencer Sumbul, Begüm Demir
This paper analyzes and compares different deep learning loss functions in the framework of multi-label remote sensing (RS) image scene classification problems. We consider seven l…
Remote Sensing Image Scene Classification with Deep Neural Networks in JPEG 2000 Compressed Domain
Akshara Preethy Byju, Gencer Sumbul, Begüm Demir +1
To reduce the storage requirements, remote sensing (RS) images are usually stored in compressed format. Existing scene classification approaches using deep neural networks (DNNs) r…