Clay weekly context brief for the Systems category (ISO week 2026-W29).

Clay tracks publications from the Systems feed list. Below are recent items from this category, each with its source and a short description of what the publication covers when one is available in the source feed.

Recent publications:
1. Partial-Reference IQA Based on Hermite-Gauss Structural Prediction and Texture Deviation
   Source: eess.IV (Image and Video Processing)
   Link: https://arxiv.org/abs/2607.08563
   We propose PreSPA (Partial-Reference Structural Prediction Approach), a Partial-Reference Image Quality Assessment framework that decomposes perceptual quality into two complementary indices.
2. Multi-UE Identification and Localization in LAWN via an Autonomous Non-Serving UAV
   Source: eess.SP (Signal Processing)
   Link: https://arxiv.org/abs/2511.13171
   This paper presents an autonomous sensing framework for identifying and localizing multiple User Equipments (UEs) in Fifth Generation (5G) cellular networks using a non-serving Unmanned Aerial Vehicle (UAV).
3. SCALMU: Synthetically-trained Coupling of Adaptive Learned Multiplicative Updates for Hyperspectral-Multispectral Fusion
   Source: eess.IV (Image and Video Processing)
   Link: https://arxiv.org/abs/2605.30973
   HyperSpectral-MultiSpectral Image (HSI-MSI) fusion aims to recover a high-resolution hyperspectral image from a low-resolution HSI and a high-resolution MSI.
4. Loss Function Design for Deep Unfolded Sparse Signal Recovery: Supervised and Unsupervised Learning
   Source: eess.SP (Signal Processing)
   Link: https://arxiv.org/abs/2509.01331
   This paper investigates the impact of loss function design in deep unfolding techniques for sparse signal recovery algorithms.
5. Quality assurance of the Federal Interagency Traumatic Brain Injury Research (FITBIR) database for multi-site MRI analysis
   Source: eess.IV (Image and Video Processing)
   Link: https://arxiv.org/abs/2512.03202
   The Federal Interagency Traumatic Brain Injury Research (FITBIR) database is a centralized data repository for traumatic brain injury (TBI) research.
6. PHINN-EEG: Topological Time-Series Analysis of Dream-State EEG -- Dynamic Betti Curves for Dream Content Classification and Topology-Conditioned Neural Signal
   Source: eess.SP (Signal Processing)
   Link: https://arxiv.org/abs/2607.09662
   Current electroencephalography (EEG)-based dream detection relies on power spectral density (PSD) and statistical moment features, achieving a state-of-the-art area under the receiver operating characteristic curve (AUC) of approximately 0.70 on the DREAM database (Wong et al., 2025, Nature Communications).
7. HemoPIC: A Physics-Informed Cerebral Hemodynamics Digital Twin for Brain Perfusion
   Source: eess.IV (Image and Video Processing)
   Link: https://arxiv.org/abs/2607.08799
   Perfusion imaging guides clinical evaluation of stroke and brain tumors by characterizing tissue-level hemodynamics.
8. Characterization of the basin of convexity for multi-snapshot spike deconvolution via variable projection
   Source: eess.SP (Signal Processing)
   Link: https://arxiv.org/abs/2607.09593
   We study the problem of multi-snapshot spike deconvolution, where the goal is to recover the locations of sparse impulses from their noisy convolution with a known point spread function (PSF) across multiple snapshots.
9. Joint-Embedding Predictive Architecture for Solar PV Panel Fault Classification
   Source: eess.IV (Image and Video Processing)
   Link: https://arxiv.org/abs/2607.09205
   The rapid expansion of solar photovoltaic (PV) systems has increased the need for reliable and scalable fault classification, as manual inspection is impractical at scale.
10. Commissioning and Low Latency Operation of the Graph Neural Network Electromagnetic Calorimeter Trigger at the Belle II Experiment
   Source: eess.SP (Signal Processing)
   Link: https://arxiv.org/abs/2607.09347
   We present the commissioning and operation of the Graph Neural Network Electromagnetic Calorimeter Trigger Module (GNN-ETM) of the Belle II experiment at the SuperKEKB collider.
11. On Motion Blur and Deblurring in Visual Place Recognition
   Source: eess.IV (Image and Video Processing)
   Link: https://arxiv.org/abs/2412.07751
   Visual Place Recognition (VPR) in mobile robotics enables robots to localize themselves by recognizing previously visited locations using visual data.
12. Co-design approach to aperture masking for imaging through atmospheric turbulence
   Source: eess.SP (Signal Processing)
   Link: https://arxiv.org/abs/2607.09265
   Aperture masking interferometry is a technique originally designed to alleviate the influence of atmospheric turbulence on images recorded on ground-based telescopes.
13. Federated Low-Rank Koopman Learning for Multivariate Time-Series Anomaly Detection in IoT Systems
   Source: eess.SP (Signal Processing)
   Link: https://arxiv.org/abs/2607.08978
   Distributed IoT systems generate multivariate time-series streams for monitoring physical assets, servers, and embedded sensing platforms.
14. Spatial Neighboring Scattering Transform: A Cross-Channel Amplitude Coupling Measure for EEG Connectivity
   Source: eess.SP (Signal Processing)
   Link: https://arxiv.org/abs/2607.08855
   The functional organization of the brain relies on coordinated activity across spatially distributed regions, making the analysis of inter-regional dependencies fundamental.
15. Symbol-Level Precoding for Continuous-Aperture ISAC Systems
   Source: eess.SP (Signal Processing)
   Link: https://arxiv.org/abs/2607.09610
   Continuous-aperture arrays (CAPAs) offer rich electromagnetic degrees of freedom for integrated sensing and communication (ISAC), but optimizing continuous current distributions leads to challenging infinite-dimensional problems.

Sources in this brief: eess.IV (Image and Video Processing); eess.SP (Signal Processing).
Selected 15 of 26 available items for this weekly brief.