Results 191 to 200 of about 5,557,524 (366)

Deep learning-based detection of power transmission lines using YOLOv4 and YOLOv8. [PDF]

Sci Rep
Karadeniz TN, Ekici S, Avci E.
europepmc   +1 more source

Research on super-resolution reconstruction of transmission lines based on SinGAN using a single image

Xinyu Song, Yunhao Zhang, Zhe Yin, Ruijin Zhu   +3 more
openalex   +2 more sources

An Idea of Fire Risk Assessment for Electric Transmission Lines

, 2017
Qi Ying, Zhe-heng ZHOU, Fa-xian WU, Jian Ma, Wei Ren, Rui Sun, Weijie Wu, Jun Eon Yang   +7 more
openalex   +2 more sources

Microwave Sensors Based on Symmetry Properties of Resonator-Loaded Transmission Lines [PDF]

, 2015
Jordi Naqui, Ferran Martı́n
openalex   +1 more source

Engineering Porous Hollow Metal‐Poly(Heptazine Imide) Spheres: An Optimized Synthetic Strategy for Controlling Surface, Morphology, and Properties

Advanced Functional Materials, EarlyView.
Hollow poly(heptazine imide) spheres are prepared through a novel approach that integrates hard templating with ionothermal synthesis. This method enables precise control over surface area, pore volume, hydrophilicity, light absorption, band position, and metal composition. These tunable properties facilitate the customized design of semiconductors for
Lingli Ni, Erik Troschke, Henrik Vorwerk, Shiva Shahbazi Avarvand, Andreas Stihl, Nadzeya Brezhneva, Marius Hermesdorf, Desirée Leistenschneider, Felix H. Schacher, Jacob Schneidewind, Martin Oschatz   +10 more
wiley   +1 more source

Using synthetic data for pretraining partial discharge detection in overhead transmission lines. [PDF]

Sci Rep
Klein L, Fulneček J, Kabot O, Dvorský J, Prokop L.   +4 more
europepmc   +1 more source

Estimated diagonal values of the parameterized transmission matrix (left panels) and diagonal values (right panels) for different initial conditions (color lines IC1, IC2, IC3).

Santiago Rosa (12197429), Manuel A. Pulido (21192715), Juan J. Ruiz (21192718), Tadeo J. Cocucci (21192721)   +3 more
openalex   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

UAVs detect hazards with multi-directional Mamba on overhead transmission lines. [PDF]

Sci Rep
Xu C, Zheng C, Zhang J.
europepmc   +1 more source

Accurate fault location for power transmission lines [PDF]

, 1990
S. Jamali
openalex