Results 71 to 80 of about 514,554 (290)
Advanced Functional Materials, EarlyView.Automat optical inspection (AOI) techniques in semiconductor fabrication can be leveraged in battery manufacturing, enabling scalable detection and analysis of electrode‐ and cell‐level imperfections through AI‐driven analytics and a digital‐twin framework.
Jianyu Li, Ertao Hu, Wei Wei, Feifei Shi
wiley +1 more source
A Novel Classification Extension-Based Cloud Detection Method for Medium-Resolution Optical Images
Remote Sensing, 2020 Accurate cloud detection using medium-resolution multispectral satellite imagery (such as Landsat and Sentinel data) is always difficult due to the complex land surfaces, diverse cloud types, and limited number of available spectral bands, especially in ...
Xidong Chen +4 more
doaj +1 more source
Advanced Functional Materials, EarlyView.A Complexation‐Mediated Diffusion‐Limited Growth (CMDLG) framework is established to rationalize the anisotropic growth of lead‐free perovskites. Integrating coordination chemistry with mass transport kinetics, this study theoretically derives and experimentally validates that stable iodocuprate complexes induce a diffusion‐limited regime.
Hyunmin Lee +5 more
wiley +1 more source
Deep Learning-Based Cloud Detection for Optical Remote Sensing Images: A Survey
Remote SensingIn optical remote sensing images, the presence of clouds affects the completeness of the ground observation and further affects the accuracy and efficiency of remote sensing applications.
Zhengxin Wang +7 more
doaj +1 more source
Environment Classification for Unmanned Aerial Vehicle Using Convolutional Neural Networks
Applied Sciences, 2020 Environment classification is one of the most critical tasks for Unmanned Aerial Vehicles (UAV). Since water accumulation may destabilize UAV, clouds must be detected and avoided. In a previous work presented by the authors, Superpixel Segmentation (SPS)
Carlos Villaseñor +5 more
doaj +1 more source
Earth and Space Science, 2022 Cloud detection is one of important tasks in automatic ground‐based cloud observation systems with ground‐based cloud images. Most supervised methods need substantial annotated samples for model training, while the pixel‐level annotation costs a lot.
Liang Ye +4 more
doaj +1 more source
Watchword-Oriented and Time-Stamped Algorithms for Tamper-Proof Cloud Provenance Cognition
, 2014 Provenance is derivative journal information about the origin and activities of system data and processes. For a highly dynamic system like the cloud, provenance can be accurately detected and securely used in cloud digital forensic investigation ...
Imran, Asif, Nahar, Nadia, Sakib, Kazi
core +1 more source
Cloud Detection Challenge-Methods and Results
IEEE AccessAccurate cloud detection is critical for advancing atmospheric monitoring and meteorological forecasting. This paper presents the Cloud Detection Challenge, an initiative aimed at enhancing cloud detection through innovative solutions using lidar-based ceilometer data.
Alessio Barbaro Chisari +9 more
openaire +3 more sources
Electrolyte Design Strategies for Static Shuttle‐Free and Long‐Life Aqueous Zinc‐Iodine Batteries
Advanced Functional Materials, EarlyView.This review systematically summarizes recent advances in electrolyte design for static aqueous Zn‐I2 batteries, highlighting solvation regulation and interfacial engineering strategies to control reaction kinetics, suppress iodine shuttling, enhance energy density, and stabilize multi‐electron iodine redox chemistry for durable, high‐performance energy
Qianqin Zhou +3 more
wiley +1 more source
Quantifying Uncertainty in Satellite-Retrieved Land Surface Temperature from Cloud Detection Errors
Remote Sensing, 2018 Clouds remain one of the largest sources of uncertainty in remote sensing of surface temperature in the infrared, but this uncertainty has not generally been quantified.
Claire E. Bulgin +6 more
doaj +1 more source