Search Results for author: Begüm Demir

Found 26 papers, 4 papers with code

Multi-Modal Fusion Transformer for Visual Question Answering in Remote Sensing

no code implementations10 Oct 2022 Tim Siebert, Kai Norman Clasen, Mahdyar Ravanbakhsh, Begüm Demir

To make the intrinsic information of each RS image easily accessible, visual question answering (VQA) has been introduced in RS.

Question Answering Representation Learning +2

Advanced Deep Learning Architectures for Accurate Detection of Subsurface Tile Drainage Pipes from Remote Sensing Images

no code implementations5 Oct 2022 Tom-Lukas Breitkopf, Leonard W. Hackel, Mahdyar Ravanbakhsh, Anne-Karin Cooke, Sandra Willkommen, Stefan Broda, Begüm Demir

In this study, we introduce two DL-based models: i) improved U-Net architecture; and ii) Visual Transformer-based encoder-decoder in the framework of tile drainage pipe detection.

Nutrition

Satellite Image Search in AgoraEO

no code implementations23 Aug 2022 Ahmet Kerem Aksoy, Pavel Dushev, Eleni Tzirita Zacharatou, Holmer Hemsen, Marcela Charfuelan, Jorge-Arnulfo Quiané-Ruiz, Begüm Demir, Volker Markl

To address this limitation, we have recently proposed MiLaN, a content-based image retrieval approach for fast similarity search in satellite image archives.

Content-Based Image Retrieval Metric Learning +1

On the Effects of Different Types of Label Noise in Multi-Label Remote Sensing Image Classification

no code implementations28 Jul 2022 Tom Burgert, Mahdyar Ravanbakhsh, Begüm Demir

In this paper, we investigate three different noise robust CV SLC methods and adapt them to be robust for multi-label noise scenarios in RS.

Image Classification Multi-Label Classification +1

Unsupervised Contrastive Hashing for Cross-Modal Retrieval in Remote Sensing

no code implementations19 Apr 2022 Georgii Mikriukov, Mahdyar Ravanbakhsh, Begüm Demir

To address this problem, in this paper we introduce a novel unsupervised cross-modal contrastive hashing (DUCH) method for text-image retrieval in RS.

Binarization Cross-Modal Retrieval +2

Coreset of Hyperspectral Images on Small Quantum Computer

no code implementations10 Apr 2022 Soronzonbold Otgonbaatar, Mihai Datcu, Begüm Demir

Moreover, we trained the SVM on the coreset data by using both a D-Wave QA and a conventional method.

An Unsupervised Cross-Modal Hashing Method Robust to Noisy Training Image-Text Correspondences in Remote Sensing

1 code implementation26 Feb 2022 Georgii Mikriukov, Mahdyar Ravanbakhsh, Begüm Demir

The proposed CHNR includes two training phases: i) meta-learning phase that uses a small portion of clean (i. e., reliable) data to train the noise detection module in an adversarial fashion; and ii) the main training phase for which the trained noise detection module is used to identify noisy correspondences while the hashing module is trained on the noisy multi-modal training set.

Meta-Learning Retrieval +1

Deep Metric Learning-Based Semi-Supervised Regression With Alternate Learning

no code implementations23 Feb 2022 Adina Zell, Gencer Sumbul, Begüm Demir

The proposed DML-S2R method aims to mitigate the problems of insufficient amount of labeled samples without collecting any additional sample with a target value.

Metric Learning regression

A Novel Self-Supervised Cross-Modal Image Retrieval Method In Remote Sensing

no code implementations23 Feb 2022 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) methods that search semantically similar images across different modalities.

Image Retrieval Retrieval

Deep Unsupervised Contrastive Hashing for Large-Scale Cross-Modal Text-Image Retrieval in Remote Sensing

no code implementations20 Jan 2022 Georgii Mikriukov, Mahdyar Ravanbakhsh, Begüm Demir

To address this problem, in this paper we introduce a novel deep unsupervised cross-modal contrastive hashing (DUCH) method for RS text-image retrieval.

Binarization Cross-Modal Retrieval +2

A Novel Framework to Jointly Compress and Index Remote Sensing Images for Efficient Content-Based Retrieval

no code implementations17 Jan 2022 Gencer Sumbul, Jun Xiang, Nimisha Thekke Madam, Begüm Demir

We also introduce a two stage learning strategy with gradient manipulation techniques to obtain image representations that are compatible with both RS image indexing and compression.

Content-Based Image Retrieval Image Compression +1

A Novel Graph-Theoretic Deep Representation Learning Method for Multi-Label Remote Sensing Image Retrieval

no code implementations1 Jun 2021 Gencer Sumbul, Begüm Demir

Unlike the other graph-based methods, the proposed method contains a novel learning strategy to train a deep neural network for automatically predicting a graph structure of each RS image in the archive.

Image Retrieval Representation Learning +1

Multi-Label Noise Robust Collaborative Learning for Remote Sensing Image Classification

1 code implementation19 Dec 2020 Ahmet Kerem Aksoy, Mahdyar Ravanbakhsh, Begüm Demir

To address this problem, the publicly available thematic products, which can include noisy labels, can be used to annotate RS images with zero-labeling cost.

Image Classification Multi-Label Classification +2

A Comparative Study of Deep Learning Loss Functions for Multi-Label Remote Sensing Image Classification

no code implementations29 Sep 2020 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.

General Classification Image Classification +2

Remote Sensing Image Scene Classification with Deep Neural Networks in JPEG 2000 Compressed Domain

no code implementations20 Jun 2020 Akshara Preethy Byju, Gencer Sumbul, Begüm Demir, Lorenzo Bruzzone

This is achieved by taking codestreams associated with the coarsest resolution wavelet sub-band as input to approximate finer resolution sub-bands using a number of transposed convolutional layers.

Classification General Classification +1

SD-RSIC: Summarization Driven Deep Remote Sensing Image Captioning

no code implementations15 Jun 2020 Gencer Sumbul, Sonali Nayak, Begüm Demir

The first step obtains the standard image captions by jointly exploiting convolutional neural networks (CNNs) with long short-term memory (LSTM) networks.

Image Captioning

Deep Learning for Image Search and Retrieval in Large Remote Sensing Archives

no code implementations3 Apr 2020 Gencer Sumbul, Jian Kang, Begüm Demir

This chapter presents recent advances in content based image search and retrieval (CBIR) systems in remote sensing (RS) for fast and accurate information discovery from massive data archives.

Image Retrieval Retrieval

Learning Convolutional Sparse Coding on Complex Domain for Interferometric Phase Restoration

no code implementations6 Mar 2020 Jian Kang, Danfeng Hong, Jialin Liu, Gerald Baier, Naoto Yokoya, Begüm Demir

Interferometric phase restoration has been investigated for decades and most of the state-of-the-art methods have achieved promising performances for InSAR phase restoration.

An Approach to Super-Resolution of Sentinel-2 Images Based on Generative Adversarial Networks

no code implementations12 Dec 2019 Kexin Zhang, Gencer Sumbul, Begüm Demir

Then, we formulate the adversarial learning of the generator and discriminator networks as a min-max game.

Super-Resolution

Metric-Learning based Deep Hashing Network for Content Based Retrieval of Remote Sensing Images

1 code implementation2 Apr 2019 Subhankar Roy, Enver Sangineto, Begüm Demir, Nicu Sebe

Hashing methods have been recently found very effective in retrieval of remote sensing (RS) images due to their computational efficiency and fast search speed.

Metric Learning Retrieval

A Novel Multi-Attention Driven System For Multi-Label Remote Sensing Image Classification

no code implementations28 Feb 2019 Gencer Sumbul, Begüm Demir

The first module aims to extract preliminary local descriptors of RS image bands that can be associated to different spatial resolutions.

General Classification Image Classification +1

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