Clay weekly context brief for the Systems category (ISO week 2026-W31).

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. Low-Altitude Channel Multipath Prediction via Panoramic Perception and Vision-Language Model
   Source: eess.SP (Signal Processing)
   Link: https://arxiv.org/abs/2607.21953
   Unmanned aerial vehicle (UAV) communication is expected to support a wide range of low-altitude applications in 6G mobile networks.
2. Geometry Calibration in Tomography with a Differentiable Ray-Based Model
   Source: eess.IV (Image and Video Processing)
   Link: https://arxiv.org/abs/2606.21405
   Geometric misalignments between the nominal and true acquisition parameters in tomography degrade reconstructions.
3. Remedying Coarsening-Based GNN Training under Heterophily via Adaptive Complementary Enhancement
   Source: eess.SP (Signal Processing)
   Link: https://arxiv.org/abs/2607.21885
   Coarsening-based training for graph neural networks (GNNs), i.e.\ training on coarsened graphs rather than the original large ones, has become a promising direction for scaling GNNs to massive graphs.
4. GeoDiff-SAR: A Geometric Prior Guided Diffusion Model for SAR Image Generation
   Source: eess.IV (Image and Video Processing)
   Link: https://arxiv.org/abs/2601.03499
   Synthetic aperture radar (SAR) image generation can mitigate data scarcity, but controllablegeneration under sparse observation angles remains difficult.
5. Influence of Electrohydrodynamic on Droplet Stability in Leaky Dielectric Media
   Source: eess.SP (Signal Processing)
   Link: https://arxiv.org/abs/2607.21638
   This work examines the deformation dynamics of dielectric liquid droplet when exposed to a uniform electric field.
6. Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction
   Source: eess.IV (Image and Video Processing)
   Link: https://arxiv.org/abs/2508.13826
   Cardiac Magnetic Resonance (CMR) imaging is a critical tool for diagnosing and managing cardiovascular disease, yet its utility is often limited by the sparse acquisition of 2D short-axis slices, resulting in incomplete volumetric information.
7. Uncertainty-Aware Fusion for Resilient Distributed Radar Sensing
   Source: eess.SP (Signal Processing)
   Link: https://arxiv.org/abs/2607.22357
   Distributed radar sensing enables safe and resilient operation in mobile robotic and vehicular systems by combining multiple local views of the scene.
8. Joint Lossless Compression and Steganography for Medical Images via Large Language Models
   Source: eess.IV (Image and Video Processing)
   Link: https://arxiv.org/abs/2508.01782
   Recently, large language models (LLMs) have driven promising progress in lossless image compression.
9. Depthwise Separable CNN for D-MIMO Indoor Localization with Data Reduction
   Source: eess.SP (Signal Processing)
   Link: https://arxiv.org/abs/2607.22217
   Indoor localization using Distributed Multiple-Input Multiple-Output (D-MIMO) and machine learning (ML) achieves sub-centimeter accuracy but faces midhaul capacity bottlenecks when transmitting raw Channel State Information (CSI) in Open Radio Access Networks (O-RAN) architectures.
10. Time-Reversed Imaging: A Multimodal Benchmark and Framework for Reconstructing Past Human-Environment Interactions
   Source: eess.IV (Image and Video Processing)
   Link: https://arxiv.org/abs/2607.22352
   We introduce time-reversed imaging, a new paradigm that infers what just happened in a scene from fading multimodal traces.
11. Ultra-wideband statistical propagation channel model for implant sensors in the human chest
   Source: eess.SP (Signal Processing)
   Link: https://arxiv.org/abs/2607.22210
   Implant medical wireless sensors for monitoring physiological parameters, automatic drug provision, and so on represent a new promising healthcare technology.
12. Farmland Extent and Visible Boundary Mapping from 1 m NAIP Imagery Using Residual U-Net and Text-Prompted SAM 3 Refinement
   Source: eess.IV (Image and Video Processing)
   Link: https://arxiv.org/abs/2607.21881
   Agricultural field maps are often proprietary, incomplete, or outdated, yet they provide the spatial framework for crop monitoring, production accounting, and land-conversion analysis.
13. A Foundation Model for Cross-Band CSI Reconstruction
   Source: eess.SP (Signal Processing)
   Link: https://arxiv.org/abs/2607.22204
   Acquiring dense high-frequency channel state information (CSI) is costly in multi-band low-altitude wireless systems because pilot resources are limited and channel dimensions change with the carrier frequency, bandwidth, and antenna array size.
14. Toward High-Fidelity 3D Point-Cloud Learning for Brain Folding Morphology Prediction Using Trans-Unet
   Source: eess.IV (Image and Video Processing)
   Link: https://arxiv.org/abs/2607.21840
   Learning high-fidelity point-cloud features in the 3D space poses significant challenges, including permutation invariance, lack of local context, difficulty in fine-grained surface reconstruction, and high computational cost.
15. Propagation models for IEEE 802.15.6 standardization of implant communication in body area networks
   Source: eess.SP (Signal Processing)
   Link: https://arxiv.org/abs/2607.22197
   A body area network is a radio communication protocol for short-range, low-power, and highly reliable wireless communication for use on the surface, inside, or in the peripheral proximity of the human body.
16. Quantum Adaptive Sensing for Accelerated MRI
   Source: eess.IV (Image and Video Processing)
   Link: https://arxiv.org/abs/2607.21737
   Compressed sensing accelerates MRI by reconstructing images from undersampled k-space, but performance depends strongly on sampling distribution.
17. Group-Connected Riemannian Manifold Optimization for Reciprocal BD-RIS
   Source: eess.SP (Signal Processing)
   Link: https://arxiv.org/abs/2607.22170
   Reconfigurable intelligent surfaces (RISs) provide a flexible means of engineering wireless propagation channels through configurable multiport scattering networks.

Sources in this brief: eess.IV (Image and Video Processing); eess.SP (Signal Processing).
Selected 17 of 29 available items for this weekly brief.