Burhaneddin Yaman
Orcid: 0000-0003-0791-5900
According to our database1,
Burhaneddin Yaman
authored at least 42 papers
between 2017 and 2024.
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Bibliography
2024
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
PaPr: Training-Free One-Step Patch Pruning with Lightweight ConvNets for Faster Inference.
Proceedings of the Computer Vision - ECCV 2024, 2024
CLIP-BEVFormer: Enhancing Multi-View Image-Based BEV Detector with Ground Truth Flow.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
2023
Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging: Combining physics and machine learning for improved medical imaging.
IEEE Signal Process. Mag., 2023
CoRR, 2023
High-Quality 0.5mm Isotropic fMRI: Random Matrix Theory Meets Physics-Driven Deep Learning.
Proceedings of the 11th International IEEE/EMBS Conference on Neural Engineering, 2023
High-fidelity Database-free Deep Learning Reconstruction for Real-time Cine Cardiac MRI.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
Unsupervised Deep Learning Methods for Biological Image Reconstruction and Enhancement: An overview from a signal processing perspective.
IEEE Signal Process. Mag., 2022
CoRR, 2022
Distributed Memory-Efficient Physics-Guided Deep Learning Reconstruction for Large-Scale 3d Non-Cartesian MRI.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Signal-Intensity Informed Multi-Coil MRI Encoding Operator for Improved Physics-Guided Deep Learning Reconstruction of Dynamic Contrast-Enhanced MRI.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022
2021
End-to-End AI-based MRI Reconstruction and Lesion Detection Pipeline for Evaluation of Deep Learning Image Reconstruction.
CoRR, 2021
fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data.
CoRR, 2021
On Instabilities of Conventional Multi-Coil MRI Reconstruction to Small Adverserial Perturbations.
CoRR, 2021
CoRR, 2021
Self-Supervised Physics-Guided Deep Learning Reconstruction for High-Resolution 3D LGE CMR.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021
Ground-Truth Free Multi-Mask Self-Supervised Physics-Guided Deep Learning in Highly Accelerated MRI.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021
Improved Supervised Training of Physics-Guided Deep Learning Image Reconstruction with Multi-Masking.
Proceedings of the IEEE International Conference on Acoustics, 2021
Compressed Sensing MRI with ℓ1-Wavelet Reconstruction Revisited Using Modern Data Science Tools.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021
20-fold Accelerated 7T fMRI Using Referenceless Self-Supervised Deep Learning Reconstruction.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021
Instabilities in Conventional Multi-Coil MRI Reconstruction with Small Adversarial Perturbations.
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021
Efficient Training of 3D Unrolled Neural Networks for MRI Reconstruction Using Small Databases.
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021
Improved Simultaneous Multi-Slice Functional MRI Using Self-supervised Deep Learning.
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021
2020
Low-Rank Tensor Models for Improved Multidimensional MRI: Application to Dynamic Cardiac T<sub>1</sub> Mapping.
IEEE Trans. Computational Imaging, 2020
Dense Recurrent Neural Networks for Accelerated MRI: History-Cognizant Unrolling of Optimization Algorithms.
IEEE J. Sel. Top. Signal Process., 2020
Multi-Mask Self-Supervised Learning for Physics-Guided Neural Networks in Highly Accelerated MRI.
CoRR, 2020
Self-Supervised Physics-Based Deep Learning MRI Reconstruction Without Fully-Sampled Data.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020
Scan-Specific Accelerated Mri Reconstruction Using Recurrent Neural Networks In A Regularized Self-Consistent Framework.
Proceedings of the 2020 IEEE 17th International Symposium on Biomedical Imaging Workshops (ISBI Workshops), 2020
High-Fidelity Accelerated MRI Reconstruction by Scan-Specific Fine-Tuning of Physics-Based Neural Networks.
Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020
2019
Self-Supervised Learning of Physics-Based Reconstruction Neural Networks without Fully-Sampled Reference Data.
CoRR, 2019
Dense Recurrent Neural Networks for Inverse Problems: History-Cognizant Unrolling of Optimization Algorithms.
CoRR, 2019
2017
Unified outage performance analysis of two-way/one-way full-duplex/half-duplex fixed-gain AF relay systems.
Proceedings of the 24th International Conference on Telecommunications, 2017
Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017