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· Zenodo (CERN European Organi...· 0 citations
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.· Frontiers in Plant Science· 0 citations
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· Zenodo (CERN European Organi...· 0 citations
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.· Zenodo (CERN European Organi...· 0 citations
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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· Zenodo (CERN European Organi...· 0 citations
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...
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.· Hardware· 0 citations
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· Research Portal (Queen's Uni...· 0 citations
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· Zenodo (CERN European Organi...· 0 citations
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· Zenodo (CERN European Organi...· 0 citations
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· Research Portal (Queen's Uni...· 0 citations
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.
MIT News · Artificial Intelligence· news.mit.eduOct 2, 2026