output
20162025
most citedImage Classification with Deep Learning in the Presence of Noisy Labels: A Survey

349 citations

45 papers

math.NA2025

A Novel Highly Parallelizable Machine-Learning Based Method for the Fast Solution of Integral Equations for Electromagnetic Scattering Problems

Enes Koç, Mert Kalfa, Secil E. Dogan +1

We propose a novel method for the efficient and accurate iterative solution of frequency domain integral equations (IEs) that are used for large/multi-scale electromagnetic scatter…

cs.SE2024★ 2 cited

Logical analysis and contradiction detection in high-level requirements during the review process using sat-solver

Simge Yatkın, Tolga Ovatman

DO-178C stands out as a guiding standard for aviation system development processes. This standard not only mandates ensuring the consistency of requirements in the software verific…

cs.CV2023★ 43 cited

HyperE2VID: Improving Event-Based Video Reconstruction via Hypernetworks

Burak Ercan, Onur Eker, Canberk Saglam +2

Event-based cameras are becoming increasingly popular for their ability to capture high-speed motion with low latency and high dynamic range. However, generating videos from events…

cs.CV2023★ 20 cited

EVREAL: Towards a Comprehensive Benchmark and Analysis Suite for Event-based Video Reconstruction

Burak Ercan, Onur Eker, Aykut Erdem +1

Event cameras are a new type of vision sensor that incorporates asynchronous and independent pixels, offering advantages over traditional frame-based cameras such as high dynamic r…

cs.LG2023★ 3 cited

Reinforcement Learning Based Self-play and State Stacking Techniques for Noisy Air Combat Environment

Ahmet Semih Tasbas, Safa Onur Sahin, Nazim Kemal Ure

Reinforcement learning (RL) has recently proven itself as a powerful instrument for solving complex problems and even surpassed human performance in several challenging application…

cs.LG2022★ 2 cited

gSuite: A Flexible and Framework Independent Benchmark Suite for Graph Neural Network Inference on GPUs

Taha Tekdoğan, Serkan Göktaş, Ayse Yilmazer-Metin

As the interest to Graph Neural Networks (GNNs) is growing, the importance of benchmarking and performance characterization studies of GNNs is increasing. So far, we have seen many…