39 citations · 87 across the 16 of their papers we have counts for
17 papers
SSM-Attack: Learning Where to Perturb for Black-Box Face Privacy
Tunahan Parlayıcı, Erchan Aptoula, Yücel Saygın
Face recognition systems are deployed widely enough that a photograph shared online can be matched without its subject's consent. Generator-based protection methods rely on heavy p…
Label-Decoupled Style Augmentation for Domain Generalization in Multi-Label Remote Sensing Scene Classification
Alaa Almouradi, Erchan Aptoula
Multi-label classification assigns several co-occurring labels to each aerial scene, yet deployed models often encounter data distributions different from their training. Feature-s…
Higher-Order Domain Generalization in Magnetic Resonance-Based Assessment of Alzheimer's Disease
Zobia Batool, Diala Lteif, Vijaya B. Kolachalama +2
Despite progress in deep learning for Alzheimer's disease (AD) diagnostics, models trained on structural magnetic resonance imaging (sMRI) often do not perform well when applied to…
MARC: Multi-Label Adaptive Retrieval Contrastive Loss for Remote Sensing Images
Amna Amir, Erchan Aptoula
Semantic overlap among land-cover categories, highly imbalanced label distributions, and complex inter-class co-occurrence patterns constitute significant challenges for multi-labe…
Text-conditioned State Space Model For Domain-generalized Change Detection Visual Question Answering
Elman Ghazaei, Erchan Aptoula
The Earth's surface is constantly changing, and detecting these changes provides valuable insights that benefit various aspects of human society. While traditional change detection…
Open-Set Domain Generalization through Spectral-Spatial Uncertainty Disentanglement for Hyperspectral Image Classification
Amirreza Khoshbakht, Erchan Aptoula
Open-set domain generalization (OSDG) tackles the dual challenge of recognizing unknown classes while simultaneously striving to generalize across unseen domains without using targ…
Single Domain Generalization for Alzheimer's Detection from 3D MRIs with Pseudo-Morphological Augmentations and Contrastive Learning
Zobia Batool, Huseyin Ozkan, Erchan Aptoula
Although Alzheimer's disease detection via MRIs has advanced significantly thanks to contemporary deep learning models, challenges such as class imbalance, protocol variations, and…
Distance Transform Guided Mixup for Alzheimer's Detection
Zobia Batool, Huseyin Ozkan, Erchan Aptoula
Alzheimer's detection efforts aim to develop accurate models for early disease diagnosis. Significant advances have been achieved with convolutional neural networks and vision tran…
Efficient Remote Sensing Change Detection with Change State Space Models
Elman Ghazaei, Erchan Aptoula
Despite their frequent use for change detection, both ConvNets and Vision transformers (ViT) exhibit well-known limitations, namely the former struggle to model long-range dependen…
Adapting the Biological SSVEP Response to Artificial Neural Networks
Emirhan Böge, Yasemin Gunindi, Erchan Aptoula +2
Neuron importance assessment is crucial for understanding the inner workings of artificial neural networks (ANNs) and improving their interpretability and efficiency. This paper in…
Explainable AI for Earth Observation: Current Methods, Open Challenges, and Opportunities
Gulsen Taskin, Erchan Aptoula, Alp Ertürk
Deep learning has taken by storm all fields involved in data analysis, including remote sensing for Earth observation. However, despite significant advances in terms of performance…
ADRMX: Additive Disentanglement of Domain Features with Remix Loss
Berker Demirel, Erchan Aptoula, Huseyin Ozkan
The common assumption that train and test sets follow similar distributions is often violated in deployment settings. Given multiple source domains, domain generalization aims to c…
Unsupervised Domain Adaptation for Semantic Segmentation using One-shot Image-to-Image Translation via Latent Representation Mixing
Sarmad F. Ismael, Koray Kayabol, Erchan Aptoula
Domain adaptation is one of the prominent strategies for handling both domain shift, that is widely encountered in large-scale land use/land cover map calculation, and the scarcity…
Domain Generalisation for Object Detection under Covariate and Concept Shift
Karthik Seemakurthy, Erchan Aptoula, Charles Fox +1
Domain generalisation aims to promote the learning of domain-invariant features while suppressing domain-specific features, so that a model can generalise better to previously unse…
Classification of remote sensing images using attribute profiles and feature profiles from different trees: a comparative study
Minh-Tan Pham, Erchan Aptoula, Sébastien Lefèvre
The motivation of this paper is to conduct a comparative study on remote sensing image classification using the morphological attribute profiles (APs) and feature profiles (FPs) ge…
Recent Developments from Attribute Profiles for Remote Sensing Image Classification
Minh-Tan Pham, Sébastien Lefèvre, Erchan Aptoula +1
Morphological attribute profiles (APs) are among the most effective methods to model the spatial and contextual information for the analysis of remote sensing images, especially fo…
GMM-Based Synthetic Samples for Classification of Hyperspectral Images With Limited Training Data
AmirAbbas Davari, Erchan Aptoula, Berrin Yanikoglu +2
The amount of training data that is required to train a classifier scales with the dimensionality of the feature data. In hyperspectral remote sensing, feature data can potentially…