566 citations · 839 across the 37 of their papers we have counts for
41 papers
Robust Logical Anomaly Detection under Capture Shifts via Synthetic Anomalies
Ufuk Efe, Alptekin Temizel
Detectors of logical anomalies, such as missing, extra or wrongly combined parts, usually score a test image by its distance from normal (good) images. They achieve near-perfect im…
Colorectal Cancer Segmentation with Adaptive Augmentation and Multi-Resolution Ensemble Models
Ümit Mert Çağlar, Alptekin Temizel
Colorectal cancer (CRC) is the second most deadly and third most common cancer, and the leading cause of death among gastrointestinal cancers. Early diagnosis is crucial for the tr…
Benchmarking the Alignment of Data-Quality Metrics, Human Judgment and Land-Cover Segmentation Performance for Earth Observation
Ümit Mert Çağlar, Alptekin Temizel
Volume and quality of datasets are crucial for deep learning model training, yet they are often constrained by availability and data acquisition costs. Synthetic data augmentation…
BELDE: Building a Large-scale Earth-observation Land-cover Dataset for Europe
Ümit Mert Çağlar, Alptekin Temizel
Earth observation imagery plays a critical role in environmental monitoring, urban planning, disaster assessment, and climate analysis. While multi-spectral sensors are increasingl…
LALE: Lightweight-Transformer Architecture for Land-Cover Estimation
Ümit Mert Çağlar, Alptekin Temizel
Semantic segmentation of remote sensing imagery requires models that capture both global context and local detail under tight computational budgets. Prior work typically optimizes…
SenBen: Sensitive Scene Graphs for Explainable Content Moderation
Fatih Cagatay Akyon, Alptekin Temizel
Content moderation systems classify images as safe or unsafe but lack spatial grounding and interpretability: they cannot explain what sensitive behavior was detected, who is invol…
Disentangled Anatomy-Disease Diffusion (DADD) for Controllable Ulcerative Colitis Progression Synthesis
Umut Dundar, Alptekin Temizel
Synthesizing longitudinal medical images at controllable disease stages while preserving patient-specific anatomy is hindered by the entanglement of pathological textures and struc…
Grounding Synthetic Data Generation With Vision and Language Models
Ümit Mert Çağlar, Alptekin Temizel
Deep learning models benefit from increasing data diversity and volume, motivating synthetic data augmentation to improve existing datasets. However, existing evaluation metrics fo…
TopoMaskV3: 3D Mask Head with Dense Offset and Height Predictions for Road Topology Understanding
Muhammet Esat Kalfaoglu, Halil Ibrahim Ozturk, Ozsel Kilinc +1
Mask-based paradigms for road topology understanding, such as TopoMaskV2, offer a complementary alternative to query-based methods by generating centerlines via a dense rasterized…
DuSCN-FusionNet: An Interpretable Dual-Channel Structural Covariance Fusion Framework for ADHD Classification Using Structural MRI
Qurat Ul Ain, Alptekin Temizel, Soyiba Jawed
Attention Deficit Hyperactivity Disorder (ADHD) is a highly prevalent neurodevelopmental condition; however, its neurobiological diagnosis remains challenging due to the lack of re…
D-GATNet: Interpretable Temporal Graph Attention Learning for ADHD Identification Using Dynamic Functional Connectivity
Qurat Ul Ain, Alptekin Temizel, Soyiba Jawed
Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder whose neuroimaging-based diagnosis remains challenging due to complex time-varying disrup…
Local-Global Prompt Learning via Sparse Optimal Transport
Deniz Kizaroğlu, Ülku Tuncer Küçüktas, Emre Çakmakyurdu +1
Few-shot adaptation of vision-language models (VLMs) like CLIP typically relies on learning textual prompts matched to global image embeddings. Recent works extend this paradigm by…
Colorectal Cancer Tumor Grade Segmentation in Digital Histopathology Images: From Giga to Mini Challenge
Alper Bahcekapili, Duygu Arslan, Umut Ozdemir +16
Colorectal cancer (CRC) is the third most diagnosed cancer and the second leading cause of cancer-related death worldwide. Accurate histopathological grading of CRC is essential fo…
Class Distance Weighted Cross Entropy Loss for Classification of Disease Severity
Gorkem Polat, Ümit Mert Çağlar, Alptekin Temizel
Assessing disease severity with ordinal classes, where each class reflects increasing severity levels, benefits from loss functions designed for this ordinal structure. Traditional…
TopoBDA: Towards Bezier Deformable Attention for Road Topology Understanding
Muhammet Esat Kalfaoglu, Halil Ibrahim Ozturk, Ozsel Kilinc +1
Understanding road topology is crucial for autonomous driving. This paper introduces TopoBDA (Topology with Bezier Deformable Attention), a novel approach that enhances road topolo…
Adaptive Augmentation Policy Optimization with LLM Feedback
Ant Duru, Alptekin Temizel
Data augmentation is a critical component of deep learning pipelines, enhancing model generalization by increasing dataset diversity. Traditional augmentation strategies rely on ma…
TopoMaskV2: Enhanced Instance-Mask-Based Formulation for the Road Topology Problem
M. Esat Kalfaoglu, Halil Ibrahim Ozturk, Ozsel Kilinc +1
Recently, the centerline has become a popular representation of lanes due to its advantages in solving the road topology problem. To enhance centerline prediction, we have develope…
State-of-the-Art in Nudity Classification: A Comparative Analysis
Fatih Cagatay Akyon, Alptekin Temizel
This paper presents a comparative analysis of existing nudity classification techniques for classifying images based on the presence of nudity, with a focus on their application in…
Ulcerative Colitis Mayo Endoscopic Scoring Classification with Active Learning and Generative Data Augmentation
Ümit Mert Çağlar, Alperen İnci, Oğuz Hanoğlu +2
Endoscopic imaging is commonly used to diagnose Ulcerative Colitis (UC) and classify its severity. It has been shown that deep learning based methods are effective in automated ana…
Adversarial Image Generation by Spatial Transformation in Perceptual Colorspaces
Ayberk Aydin, Alptekin Temizel
Deep neural networks are known to be vulnerable to adversarial perturbations. The amount of these perturbations are generally quantified using metrics, such as , a…
TopoMask: Instance-Mask-Based Formulation for the Road Topology Problem via Transformer-Based Architecture
M. Esat Kalfaoglu, Halil Ibrahim Ozturk, Ozsel Kilinc +1
Driving scene understanding task involves detecting static elements such as lanes, traffic signs, and traffic lights, and their relationships with each other. To facilitate the dev…
Deep Architectures for Content Moderation and Movie Content Rating
Fatih Cagatay Akyon, Alptekin Temizel
Rating a video based on its content is an important step for classifying video age categories. Movie content rating and TV show rating are the two most common rating systems establ…
Sequence Models for Drone vs Bird Classification
Fatih Cagatay Akyon, Erdem Akagunduz, Sinan Onur Altinuc +1
Drone detection has become an essential task in object detection as drone costs have decreased and drone technology has improved. It is, however, difficult to detect distant drones…
Evaluation and Analysis of Different Aggregation and Hyperparameter Selection Methods for Federated Brain Tumor Segmentation
Ece Isik-Polat, Gorkem Polat, Altan Kocyigit +1
Availability of large, diverse, and multi-national datasets is crucial for the development of effective and clinically applicable AI systems in the medical imaging domain. However,…