相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。In-situ monitoring of melt pool images for porosity prediction in directed energy deposition processes
Mojtaba Khanzadeh et al.
IISE TRANSACTIONS (2019)
From in-situ monitoring toward high-throughput process control: cost-driven decision-making framework for laser-based additive manufacturing
Ruholla Jafari-Marandi et al.
JOURNAL OF MANUFACTURING SYSTEMS (2019)
Finite-element simulation of melt pool geometry and dilution ratio during laser cladding
Hucheng Tian et al.
APPLIED PHYSICS A-MATERIALS SCIENCE & PROCESSING (2019)
Layer-Wise Modeling and Anomaly Detection for Laser-Based Additive Manufacturing
Seyyed Hadi Seifi et al.
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME (2019)
Layerwise Anomaly Detection in Laser Powder-Bed Fusion Metal Additive Manufacturing
Mohamad Mahmoudi et al.
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME (2019)
Defect detection in selective laser melting technology by acoustic signals with deep belief networks
Dongsen Ye et al.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY (2018)
Deep learning for smart manufacturing: Methods and applications
Jinjiang Wang et al.
JOURNAL OF MANUFACTURING SYSTEMS (2018)
Porosity prediction: Supervised-learning of thermal history for direct laser deposition
Mojtaba Khanzadeh et al.
JOURNAL OF MANUFACTURING SYSTEMS (2018)
Review on thermal analysis in laser-based additive manufacturing
Zhaorui Yan et al.
OPTICS AND LASER TECHNOLOGY (2018)
Determination of melt pool dimensions using DOE-FEM and RSM with process window during SLM of Ti6Al4V powder
Jyun-Rong Zhuang et al.
OPTICS AND LASER TECHNOLOGY (2018)
Virtualization and deep recognition for system fault classification
Peng Wang et al.
JOURNAL OF MANUFACTURING SYSTEMS (2017)
A deep learning-based approach to material removal rate prediction in polishing
Peng Wang et al.
CIRP ANNALS-MANUFACTURING TECHNOLOGY (2017)
ImageNet Classification with Deep Convolutional Neural Networks
Alex Krizhevsky et al.
COMMUNICATIONS OF THE ACM (2017)
Falcon: Visual analysis of large, irregularly sampled, and multivariate time series data in additive manufacturing
Chad A. Steed et al.
COMPUTERS & GRAPHICS-UK (2017)
Design of deep convolutional neural network architectures for automated feature extraction in industrial inspection
Daniel Weimer et al.
CIRP ANNALS-MANUFACTURING TECHNOLOGY (2016)
Data indicating temperature response of Ti-6Al-4V thin-walled structure during its additive manufacture via Laser Engineered Net Shaping
Garrett J. Marshall et al.
DATA IN BRIEF (2016)
Deep Neural Networks for Acoustic Modeling in Speech Recognition
Geoffrey Hinton et al.
IEEE SIGNAL PROCESSING MAGAZINE (2012)
How to avoid over-fitting in multivariate calibration -: The conventional validation approach and an alternative
N. M. Faber et al.
ANALYTICA CHIMICA ACTA (2007)
分享论文
