中国矿业大学主页平台系统 liucancan--Home-- Intelligent recognition and identification of fracture types and parameters for borehole images based on developed convolutional neural networks and post-processing

Home > Scientific Research > Paper Publications

Intelligent recognition and identification of fracture types and parameters for borehole images based on developed convolutional neural networks and post-processing

Release time:2024-11-01 Hits:

DOI number:10.1016/j.engfracmech.2023.109624
Affiliation of Author(s):矿业工程学院
Funded by:国家自然科学基金项目
First Author:liucancan
Co-author:Kim, Jineon,Jae-Joon Song,zhengxigui,NIAZ MUHAMMAD,NASIR KHAN,郭晓玮
Indexed by:Journal paper
Volume:v 292,
ISSN No.:00137944
Translation or Not:no
Date of Publication:2023-11-15

Pre One:基于钻孔成像的结构面智能化识别系统附视频

Next One:Fracture Identification Under Unstable Drilling Conditions Based on Proposed Multi-parameter Voting Method

Home

Scientific Research

Teaching Research

Awards and Honours

Enrollment Information

Student Information

My Album

Blog

Personal Information

Other Contact Information

Intelligent recognition and identification of fracture types and parameters for borehole images based on developed convolutional neural networks and post-processing