Author

M. Gabbouj

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Open access Aug 2026

Blind Image Quality Assessment via a Hierarchical Perceptual Modulation Network

Blind image quality assessment (BIQA) is crucial for perceptual optimization in image processing. To better align objective quality predictions with human perception, researchers have designed BIQA models inspired by the frequency-sensitive characteristics of the human visual system (HVS). However, existing methods usu...

Li Yu, Yifan Bao, Jun-Yan Li et al. · ACM Transactions on Multimed... · 0 citations

#artificial intelligence Preprint Sep 2026

You've Seen Enough: Quality-Constrained Image Coding for Machines

This paper proposes two variants of a penalty function that guides the quality toward the target: an absolute function and a bilinear function, the latter applying a steeper slope once the target visual quality is exceeded.

Khoa Pham-Dinh, Sanaz Nami, H. R. Tavakoli et al. · 0 citations

2026

DFF-Net: An Efficient Target Detection Network With Deep Feature Extraction for Underwater Sonar Images

Vision-based perception models have been widely used for target detection in underwater sonar imagery. However, due to environmental constraints and hardware limitations, existing models often struggle to capture discriminative deep features in low-resolution sonar images. To address this issue, we propose a novel deep...

Pengfei Bi, Yi Ding, Xue Du et al. · IEEE Transactions on Instrum... · 0 citations

Aug 2026

Introduction to the Special Issue on Large Action Models (LAMs): Theory, Implementation, and Applications

Five contributions addressing key challenges in LAM research are brought together, including safety and robustness against jailbreak and adversarial attacks, semantic-perceptual integration for robotic manipulation, efficient deployment on edge devices, and natural-language-driven decision-making for networked systems.

M. Gabbouj, Jin Li, Xin Lin et al. · ACM Transactions on Multimed... · 0 citations

#machine learning Preprint Sep 2026

Multi-Pass, Multi-View Blended Learning for High-Fidelity Volumetric CT Synthesis from Chest X-Rays

A Multi-Pass Multi-View Blended Learning framework for synthesizing high-fidelity volumetric CT directly from real chest X-ray (CXR) images that mitigates the synthetic-to-real domain gap while enhancing both the structural integrity and anatomical detail of the final output.

Ozer Can Devecioglu, S. Kiranyaz, Rashid Mazhar et al. · 0 citations

#machine learning Open access Feb 2025

Anomaly detection in smart power grids with graph-regularized MS-SVDD: a multimodal subspace learning approach

A generalized Multimodal Subspace Support Vector Data Description model with graph-embedded regularization is proposed, illustrating how relational and structural information can be systematically embedded into one-class models, enabling robust learning under complex, high-dimensional, and multimodal conditions.

Thomas Debelle, F. Sohrab, Pekka Abrahamsson et al. · Scientific Reports · 1 citation