1.4k citations · 1.6k across the 26 of their papers we have counts for
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Expert Operational GANS: Towards Real-Color Underwater Image Restoration
Ozer Can Devecioglu, Serkan Kiranyaz, Mehmet Yamac +1
The wide range of deformation artifacts that arise from complex light propagation, scattering, and depth-dependent attenuation makes the underwater image restoration to remain a ch…
Blind Underwater Image Restoration using Co-Operational Regressor Networks
Ozer Can Devecioglu, Serkan Kiranyaz, Turker Ince +1
The exploration of underwater environments is essential for applications such as biological research, archaeology, and infrastructure maintenanceHowever, underwater imaging is chal…
BM3D vs 2-Layer ONN
Junaid Malik, Serkan Kiranyaz, Mehmet Yamac +1
Despite their recent success on image denoising, the need for deep and complex architectures still hinders the practical usage of CNNs. Older but computationally more efficient met…
Convolutional versus Self-Organized Operational Neural Networks for Real-World Blind Image Denoising
Junaid Malik, Serkan Kiranyaz, Mehmet Yamac +2
Real-world blind denoising poses a unique image restoration challenge due to the non-deterministic nature of the underlying noise distribution. Prevalent discriminative networks tr…
Self-Organized Operational Neural Networks for Severe Image Restoration Problems
Junaid Malik, Serkan Kiranyaz, Moncef Gabbouj
Discriminative learning based on convolutional neural networks (CNNs) aims to perform image restoration by learning from training examples of noisy-clean image pairs. It has become…
3D Quantum Cuts for Automatic Segmentation of Porous Media in Tomography Images
Junaid Malik, Serkan Kiranyaz, Riyadh Al-Raoush +7
Binary segmentation of volumetric images of porous media is a crucial step towards gaining a deeper understanding of the factors governing biogeochemical processes at minute scales…