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edge computing

2,418 papers

#edge computing Book Open access Oct 2026

A Zero-Shot Multi-Scope Life Cycle Assessment Framework for Machine Learning: Unifying Carbon, Water, and Network Footprints

Machine learning workloads now consume a significant and increasing percentage of global data centers energy. To overcome this problem, researchers and developers of new AI applications and pipelines are forced to use post hoc techniques and approaches to power telemetry to measure the actual power consumption during m...

Anonymous 2 Anonymous2 · 0 citations
#edge computing Open access Oct 2026

Edge-deployable greenhouse tomato cluster harvesting robot integrating YOLOv8n-BiFPN-WIoU and ROS-based autonomous control

To develop an edge-deployable greenhouse tomato cluster harvesting robot capable of accurate fruit detection, three-dimensional localization, autonomous navigation, and robotic harvesting under complex greenhouse conditions. The objective was to improve detection performance under fruit occlusion and variable illum...

Fan-Zhao Meng, Zhen Wang, Huan Wang et al. · 0 citations
#edge computing Open access Oct 2026

PUH Theorem 378 — A Static Core Stays at Rest: Massive Rest Is Fixed by the Cartan Involution, the Wall Bends Against Every Descent, and T342's Gravity Result Covers Every Static Core at Rest

Photonic Universe Hypothesis (PUH) — Theorem paper. THE QUESTION. T377 found that the massive states at rest meet T175's Casimir wall on a closed shell, and that T342's Theorem 342.1 — the bound that excludes the multiplier lambda as the gravity — holds for states at rest but is unproven for moving ones. Its OPEN (1) a...

Brian Martell · 0 citations
#edge computing Dataset Open access Oct 2026

Trained models and predictions for "Compact sensor-aided millimeter-wave beam prediction runs in real time on low-cost edge hardware"

Trained models, per-sample test predictions and analysis outputs for the revised article "Compact sensor-aided millimeter-wave beam prediction runs in real time on low-cost edge hardware" (Scientific Reports, under revision). Code: https://github.com/himansh24dev/compute-efficient-beam-prediction (branch "revision").Da...

Himanshu Sharma, Tarun Jain, Deependra Singh et al. · 0 citations
#edge computing Open access Oct 2026

究極のジェネシス・プロトコル:Q-Day後の分散型生体インフラと母乳由来生理活性成分の臨床的最終局面 (英語副題: Ultimate Genesis Protocol: Decentralized Biological Infrastructure Post-Q-Day and the Clinical Endgame of Breast Milk-Derived Bioactive Components)

日本語概要 (Japanese Abstract) 本技術論文・臨床アーキテクチャ仕様書は、単一の病理標的に対して化学合成分子を単一障害点(Single Point of Failure)として適用してきた中央集権的製薬モデルの崩壊、すなわち「生物学的Q-Day(薬害と耐性の限界点 / Chemical Monopoly Collapse)」以後の世界における、自律分散型生体インフラストラクチャ「ジ...

Yoko Hasebe · 0 citations
#edge computing Open access Oct 2026

A Hybrid Single-Shot Vision-AI and Geospatial Framework for Multimodal Infrastructure Degradation Mapping in Urban Networks

Conventional transportation infrastructure inspection is often labor-intensive, time-consuming, and limited to individual asset types, reducing the efficiency of large-scale infrastructure management. This study proposes a hybrid Vision-AI and geospatial framework for automated multimodal infrastructure deterioration d...

Mikkel Sørensen, Freja Holm · 0 citations
#edge computing Open access Oct 2026

StEdge: A Low-Power Real-Time Hardware Accelerator for Edge Detection Using Stochastic Computing

Edge detection is a fundamental operation in real-time image and video processing systems. However, conventional gradient-based hardware implementations incur significant power, area, and computational overheads. This work presents StEdge, a low-power, configurable hardware accelerator for real-time edge detection base...

Priyajit Ghosh, Rajarshi Mukherjee, Auro Anand Saha et al. · 0 citations
#edge computing Open access Oct 2026

On designing structure-aware high-performance graph algorithms

Graph algorithms find several usages in industry, science, humanities, and technology. The fast-growing size of graph datasets in the context of the processing model of the current hardware has resulted in different bottlenecks such as memory locality, work-efficiency, and load-balance that degrade the performance. To...

Mohsen Koohi Esfahani · 0 citations
#edge computing Open access Oct 2026

EMAP-SSN: Embedding- and Multiple-Alignment-integrated Protein Sequence Similarity Network Platform

EMAP-SSN v0.3.0 EMAP-SSN v0.3.0 adds 3D layout generation with reproducible seeds and an optional VR viewer, protein-property metadata computed from the input FASTA, and residue-level alignment inspection over MCP. It installs ESM and Transformers from PyPI instead of bundling wheels, moves the managed environment to P...

Xuebin Feng · 0 citations
#edge computing Open access Oct 2026

FEPCert: An Open-Source Toolkit for Quality-Control, Phase Space Overlap, and Thermodynamic Cycle Closure Certification of Alchemical Free Energy Simulations

FEPCert checks alchemical free-energy calculations and perturbation networks: thermodynamic integration (including paths in which several lambda components change) and BAR, the two-state MBAR overlap of neighbouring states, the agreement of TI with BAR on the same states (quadrature error), time convergence, and the cl...

Andres Monreal Hernandez · 0 citations
#data science Open access Oct 2026

Machine learning methods for hyperspectral imaging: from reconstruction to classification

With the growing demands for efficient and scalable food analysis, agriculture, and healthcare applications, the need for improved data acquisition and processing techniques has become increasingly significant. Near Infrared Spectroscopy has emerged as a powerful tool for non-invasive analysis in these domains, providi...

Robert Alexander Williamson · 0 citations

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Microsoft Research Blog Oct 6, 2026

What AI gets wrong and what failure teaches us

Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity.  The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.

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