most citedLow-Latency Video Anonymization for Crowd Anomaly Detection: Privacy Versus Performance

5 citations

8 papers

cs.CV2026

Fast 3D Foundation Model Initialized Gaussian Splatting

Anurag Dalal, Daniel Hagen, Kjell G. Robbersmyr +2

This paper introduces a fast method for high-quality 3D Gaussian Splatting (3DGS) reconstruction without traditional Structure-from-Motion (SfM). The proposed approach leverages 3D…

cs.LG2026

Scalable Temporal Anomaly Causality Discovery in Large Systems: Achieving Computational Efficiency with Binary Anomaly Flag Data

Mulugeta Weldezgina Asres, Christian Walter Omlin, The CMS-HCAL Collaboration

Extracting anomaly causality facilitates diagnostics once monitoring systems detect system faults. Identifying anomaly causes in large systems involves investigating a broader set…

cs.CV20265 cited

Low-Latency Video Anonymization for Crowd Anomaly Detection: Privacy Versus Performance

Mulugeta Weldezgina Asres, Lei Jiao, Christian Walter Omlin

Recent advancements in artificial intelligence hold ample potential for monitoring applications using surveillance cameras. However, concerns about privacy and model bias have made…

eess.SP2026

Explainable and Hardware-Efficient Jamming Detection for 5G Networks Using the Convolutional Tsetlin Machine

Vojtech Halenka, Mohammadreza Amini, Per-Arne Andersen +2

All applications in fifth-generation (5G) networks rely on stable radio-frequency (RF) environments to support mission-critical services in mobility, automation, and connected inte…

cond-mat.mtrl-sci2026

Spin-Seebeck Signatures of Spin Chirality in Kagome Antiferromagnets

Feodor Svetlanov Konomaev, Mithuss Tharmalingam, Kjetil M. D. Hals

Non-collinear antiferromagnets (NCAFMs) are appealing for antiferromagnetic spintronics, as they combine the advantages of collinear antiferromagnets with novel emergent phenomena…

cs.CL2026

English K_Quantization of LLMs Does Not Disproportionately Diminish Multilingual Performance

Karl Audun Borgersen, Morten Goodwin

For consumer usage of locally deployed LLMs, the GGUF format and k\_quantization are invaluable tools for maintaining the performance of the original model while reducing it to siz…