Recognition and classification of single melt tracks using deep neural network: A fast and effective method to determine process windows in selective laser melting

Metal Additive Manufacturing Parts Inspection Using Convolutional Neural Network

(2020) Wenyuan Cui et al.   Applied Sciences-Basel

In Situ Monitoring Systems of The SLM Process: On the Need to Develop Machine Learning Models for Data Processing

(2020) Pinku Yadav et al.   Crystals

Processing parameters in laser powder bed fusion metal additive manufacturing

(2020) J.P. Oliveira et al.   MATERIALS & DESIGN

Attentive neural cell instance segmentation

(2019) Jingru Yi et al.   MEDICAL IMAGE ANALYSIS

Analytical modeling of lack-of-fusion porosity in metal additive manufacturing

(2019) Jinqiang Ning et al.   APPLIED PHYSICS A-MATERIALS SCIENCE & PROCESSING

Influence of Process Parameters and Deposition Strategy on Laser Metal Deposition of 316L Powder

(2019) Federico Mazzucato et al.   Metals

Metal vapor micro-jet controls material redistribution in laser powder bed fusion additive manufacturing

(2017) Sonny Ly et al.   Scientific Reports

Deep learning

(2015) Yann LeCun et al.   NATURE

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

Review of selective laser melting: Materials and applications

(2015) C. Y. Yap et al.   Applied Physics Reviews

A new part consolidation method to embrace the design freedom of additive manufacturing

(2015) Sheng Yang et al.   Journal of Manufacturing Processes

Observation of keyhole-mode laser melting in laser powder-bed fusion additive manufacturing

(2014) Wayne E. King et al.   JOURNAL OF MATERIALS PROCESSING TECHNOLOGY

Single track formation in selective laser melting of metal powders

(2010) I. Yadroitsev et al.   JOURNAL OF MATERIALS PROCESSING TECHNOLOGY

The Pascal Visual Object Classes (VOC) Challenge

(2009) Mark Everingham et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION