2 citations · 6 across the 7 of their papers we have counts for
8 papers
Detecting Temporally Localized Manipulations in Authentic Video Streams
Okan Umur, Ali Emre Güşlü, Ibrahim Delibasoglu
The rapid advancement of video editing and generative artificial intelligence technologies has made realistic video manipulation increasingly accessible. Although existing datasets…
Cross-Domain Generalization Limits of Vision Foundation Models in Facial Deepfake Detection
Ibrahim Delibasoglu
The rapid evolution of generative models has enabled the creation of hyper-realistic facial deepfakes, exposing a critical vulnerability in modern digital forensics: the inability…
Spectral Manifold Regularization for Stable and Modular Routing in Deep MoE Architectures
Ibrahim Delibasoglu
Mixture of Experts (MoE) architectures enable efficient scaling of neural networks but suffer from expert collapse, where routing converges to a few dominant experts. This reduces…
Learning Temporal Saliency for Time Series Forecasting with Cross-Scale Attention
Ibrahim Delibasoglu, Fredrik Heintz
Explainability in time series forecasting is essential for improving model transparency and supporting informed decision-making. In this work, we present CrossScaleNet, an innovati…
Scaling Transformers for Time Series Forecasting: Do Pretrained Large Models Outperform Small-Scale Alternatives?
Sanjay Chakraborty, Ibrahim Delibasoglu, Fredrik Heintz
Large pre-trained models have demonstrated remarkable capabilities across domains, but their effectiveness in time series forecasting remains understudied. This work empirically ex…
LMS-AutoTSF: Learnable Multi-Scale Decomposition and Integrated Autocorrelation for Time Series Forecasting
Ibrahim Delibasoglu, Sanjay Chakraborty, Fredrik Heintz
Time series forecasting is an important challenge with significant applications in areas such as weather prediction, stock market analysis, scientific simulations and industrial pr…
EDformer: Embedded Decomposition Transformer for Interpretable Multivariate Time Series Predictions
Sanjay Chakraborty, Ibrahim Delibasoglu, Fredrik Heintz
Time series forecasting is a crucial challenge with significant applications in areas such as weather prediction, stock market analysis, and scientific simulations. This paper intr…
UAV Images Dataset for Moving Object Detection from Moving Cameras
Ibrahim Delibasoglu
This paper presents a new high resolution aerial images dataset in which moving objects are labelled manually. It aims to contribute to the evaluation of the moving object detectio…