defects
There are 0 repository under defects topic.
- Surface-Defect-Detection
Charmve / Surface-Defect-Detection
📈 目前最大的工业缺陷检测数据库及论文集 Constantly summarizing open source dataset and critical papers in the field of surface defect research which are of great importance.
Language:Python 3197 Ericsson / codechecker
CodeChecker is an analyzer tooling, defect database and viewer extension for static and dynamic analyzer tools.
Language:Python 2271- doped
SMTG-Bham / doped
doped is a Python software for the generation, pre-/post-processing and analysis of defect supercell calculations, implementing the defect simulation workflow in an efficient, reproducible, user-friendly yet powerful and fully-customisable manner.
Language:Python 137 WMD-group / CarrierCapture.jl
Julia package to compute trap-assisted electron and hole capture in semiconductors
Language:Jupyter Notebook 52Band structure unfolding made easy!
Language:Python 43mturiansky / nonrad
Implementation for computing nonradiative recombination rates in semiconductors
Language:Python 41noahgift / devml
Product of Pragmatic AI Labs: Machine Learning, Statistics and Utilities around Developer Productivity, Company Productivity and Project Productivity
Language:Jupyter Notebook 28orc-tuni / dark-spot-mapper
Imaging system for analyzing defects of semiconductor wafers and chips
Language:Python 22MichaelHotaling / klarfkit
Python utilities for loading, plotting, and editing wafer defect maps known as KLA Reference Files (KLARFs)
Language:Python 18polystat / awesome-bugs
A taxonomy of defects with a benchmarking script that validates which of them can be spot by which static analyzers
Language:Python 16whisperity / CodeChecker-Action
Execute static analysis through CodeChecker in the CI.
Language:Shell 15JuDFTteam / aiida-kkr
AiiDA plugin of the high-performance density functional theory code JuKKR (www.judft.de) for high-throughput electronic structure calculations.
kkraiidaworkflowforschungszentrum-juelichelectronic-structuremultiple-scatteringab-initioall-electronband-structurecoherent-potential-approximationcomputational-materials-sciencecondensed-matter-physicsdefectsdensity-functional-theoryfull-potentialgreens-functionshigh-throughputjudftmagnetismsuperconductivityLanguage:Python 14hema-ted / pyzfs
A python package to compute zero-field-splitting tensors for molecules and spin quantum bits in semiconductors.
Language:Python 11- Language:Jupyter Notebook 11
aurelitec / pixelhealer-windows
PixelHealer (for Windows) can help you try to fix dead pixels by yourself, before running back to the store!
Language:C# 10- Language:TeX 10
InjuredPixels (for Windows) can help you check your PC, laptop or tablet screen for dead pixels, scratches or defects.
Language:C# 9NeroHin / defect-detection-and-segment-deep-learning
Detection and Segmentation in Powder Spreading Process of Magnetic Material Additive Manufacturing
Language:Jupyter Notebook 8rahlk / Bellwether
Simpler Transfer Learning (Using "Bellwethers"). ARXIV link: https://arxiv.org/abs/1703.06218
Language:Python 8Howeng98 / Anomaly_Inspection_Datasets
A references and discriptions for anomaly, inspection, defect detection datasets.
Full-potential Korringa-Kohn-Rostoker Green function code JuKKR: All-electron DFT (repo mirror)
ab-initioall-electroncpadefectsdensity-functional-theorykkrmultiple-scatteringcoherent-potential-approximationcomputational-materials-sciencecondensed-matter-physicselectronic-structureforschungszentrum-juelichfull-potentialgreens-functionshpcjudftmagnetismquantum-materialsspintronicssuperconductivityLanguage:Fortran 6Computing solar energy conversion limits using the Trap Limited Conversion (TLC) metric
Language:Python 6jeffreythawkins / jira2v1
This node script searches an Atlassian JIRA instance for defects and creates a task for each in a VersionOne story. It ignores JIRAs that may have already been added from a previous run.
Language:JavaScript 5pranayshyamkuwar / NMF-For-Classification-of-Defects-on-Steel-Surface-
Non-negative matrix factorization is applied for classification of defects on steel surface using CNN
Language:Python 5dnstanciu / pool-tracker
Melt pool monitoring in a metal 3D printer. Tracks area of the melt pool, intensity, and radius. The variations of the melt pool are used to detect build defects. Meshflow Limited
Language:Jupyter Notebook 4PasaOpasen / Search-for-defects-in-plates
Application for searching for defects in plates (Ellipse method and Time-reversal)
Language:C# 4Ranjan2104 / Hand-Gesture-Recognition-System
Gesture recognition is a topic in computer science and language technology with the goal of interpreting human gestures via mathematical algorithms.[1] It is a subdiscipline of computer vision. Gestures can originate from any bodily motion or state but commonly originate from the face or hand. Current[when?] focuses in the field include emotion recognition from face and hand gesture recognition. Users can use simple gestures to control or interact with devices without physically touching them. Many approaches have been made using cameras and computer vision algorithms to interpret sign language.
Language:Python 4- Language:Jupyter Notebook 4
ncfrey / defect-design
Supplementary material accompanying Frey, N. C.; Akinwande, D.; Jariwala, D.; Shenoy, V. B. Machine Learning-Enabled Design of Point Defects in 2D Materials for Quantum and Neuromorphic Information Processing, ACS Nano (2020).
Language:Jupyter Notebook 3neerajtiwari360 / Pulse-Thermography
Material defect detection with Pulse Thermography
Language:Python 3Zixiangzann / Defect-Management---For-QA-By-QA
Defect Management website build using React
Language:JavaScript 3InjuredPixels (for Android) can help you check your entire screen for dead pixels, scratches or other defects.
Language:Java 2madvid / PhD_influence_HCN_V_defect_solubility_diffusion_O_in_Ni
Part of my work realized during the years as a PhD student. I was in the team MEMO of the CIRIMAT lab in Toulouse. I study via a multi-scale approach the influence influence of H, C, N impurities and point defects on the solubility and diffusion of the oxygen in the nickel (fcc phase). My works was under the supervision of Damien Connétable and Daniel Monceau.
- Language:JavaScript 2
