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You've Seen Enough: Quality-Constrained Image Coding for Machines
Khoa Pham-Dinh, Sanaz Nami, Hamed Rezazadegan Tavakoli +2
Visual data is increasingly consumed by machine-vision systems rather than by human observers. Image Coding for Machines (ICM) compresses images assuming the main observer is a com…
Multi-Pass, Multi-View Blended Learning for High-Fidelity Volumetric CT Synthesis from Chest X-Rays
Ozer Can Devecioglu, Serkan Kiranyaz, Rashid Mazhar +3
Reconstructing volumetric Computed Tomography (CT) from a single 2D chest radiograph (CXR) is an ill-posed inverse problem, further complicated by the scarcity of paired CXR-CT tra…
From Reports to Ontologies: Ontology-Guided Representation Learning for 12-Lead ECG
Lei Xu, Fahad Sohrab, Mehmet Yamac +2
The 12-lead electrocardiogram (ECG) is a quasi-periodic, multi-channel signal with diagnostic content spanning timescales from millisecond waveform morphology to multi-second rhyth…
Axiomatizing Neural Networks via Pursuit of Subspaces
Mehmet Yamac, Mert Duman, Ugur Akpinar +4
While deep neural networks have achieved remarkable success across a wide range of domains, their underlying mechanisms remain poorly understood, and they are often regarded as bla…
The Eleventh NTIRE 2026 Efficient Super-Resolution Challenge Report
Bin Ren, Hang Guo, Yan Shu +60
This paper reviews the NTIRE 2026 challenge on efficient single-image super-resolution with a focus on the proposed solutions and results. The aim of this challenge is to devise a…
MTS-CSNet: Multiscale Tensor Factorization for Deep Compressive Sensing on RGB Images
Mehmet Yamac, Lei Xu, Serkan Kiranyaz +1
Deep learning based compressive sensing (CS) methods typically learn sampling operators using convolutional or block wise fully connected layers, which limit receptive fields and s…