Work

Toward quantitative fractography using convolutional neural networks

Year: 2020

Type: article

Source: Engineering Fracture Mechanics

DOI: 10.1016/j.engfracmech.2020.106992

Authors: Stylianos Tsopanidis, Raúl Herrero Moreno, Shmuel Osovski

Institutions: Universidad Carlos III de Madrid, Technion – Israel Institute of Technology

Language: English

Topic: Mechanical Failure Analysis and Simulation

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funders: PAZY Foundation, Horizon 2020

OpenAlex ID: W2964732160

FWCI: 2.696

Cites: 42

Cited by: 61

Related to: 10