Author

C. Timmerer

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Preprint Sep 2026

MoQSplat: Adaptive Progressive Streaming of 3D Gaussian Splatting via MoQ

3D Gaussian Splatting (3DGS) enables photorealistic novel view synthesis, but transmitting gigabyte-scale scene data remains challenging for immersive applications. Traditional HTTP Adaptive Streaming over TCP introduces Head-of-Line (HOL) blocking and coarse segmenting ill-suited to fine-grained 3DGS delivery. We prop...

Emanuele Artioli, Mohammadreza Ghafari, Md Tariqul Islam et al. · 0 citations

Preprint Sep 2026

From Pixels to Semantics: Edge AI for UAV-Based Critical Infrastructure Inspection

This article categorizes existing UAV inspection architectures, identifies their key system challenges and architectural requirements, and experimentally assesses the feasibility of semantic edge intelligence on NVIDIA Jetson UAV-class hardware using the COCO-Bridge dataset.

Reza Farahani, Naser Hossein Motlagh, Zoha Azimi et al. · 0 citations

Preprint Sep 2026

Cloud, Edge, or Split? Profiling Onboard and Split Vision-Language Model Deployment for Drone AI

This paper benchmarks the performance trade-offs among fully onboard, cloud-based, and split-computing architectures for lightweight VLMs using SmolVLM-256M as a representative lightweight VLM and shows that no deployment strategy is universally optimal.

Zoha Azimi, Reza Farahani, S. Dustdar et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Perceptual Refinement of an End-to-End Video Streaming Pipeline via Generative AI Layers

Traditional codecs treat every region of a frame alike; a generative layer can instead degrade the regions a viewer attends to least and reconstruct them at the client. We present PRESLEY, which extends the prior conference work ELVIS by replacing destructive block removal with adaptive in-place degradation under a rem...

Emanuele Artioli, F. Tashtarian, C. Timmerer · 0 citations

Preprint Aug 2026

DRLM: Deep Reinforcement Learning-Based LLM Query Orchestration in Edge Environments

DRLM, a Deep Reinforcement Learning-based LLM query orchestration framework in edge environments shows robust and stable orchestration, and improves latency under increasing workloads up to 61.4%, demonstrating robust and stable orchestration.

Reza Farahani, Zoha Azimi Ourimi, Mario Colosi et al. · 0 citations

Conference Jul 2026

EVLM: Intent-Driven Edge Vision Language Model for UAV-Based Power Line Inspection

Inspection of critical infrastructure, such as power lines, is increasingly conducted using unmanned aerial vehicles (UAVs) that capture aerial video for subsequent human review. Although recent edge-based approaches deploy onboard object detectors to identify predefined defect classes, these pipelines remain closed-se...

Reza Farahani, Zoha Azimi, Ilir Murturi et al. · International Conference on... · 1 citation