AIMC Topic: Lasers

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Deep Learning Based Monitoring of Spatter Behavior by the Acoustic Signal in Selective Laser Melting.

Sensors (Basel, Switzerland)
As one of the most promising metal additive manufacturing (AM) technologies, the selective laser melting (SLM) process has high expectations ofr its use in aerospace, medical, and other fields. However, various defects such as spatter, crack, and por...

Performing sequential forward selection and variational autoencoder techniques in soil classification based on laser-induced breakdown spectroscopy.

Analytical methods : advancing methods and applications
The feasibility and accuracy of several combination classification models, , quadratic discriminant analysis (QDA), random forest (RF), Bernoulli naïve Bayes (BNB), and support vector machine (SVM) classification models combined with either sequentia...

Improving the Ability of a Laser Ultrasonic Wave-Based Detection of Damage on the Curved Surface of a Pipe Using a Deep Learning Technique.

Sensors (Basel, Switzerland)
With the advent of the Fourth Industrial Revolution, the economic, social, and technological demands for pipe maintenance are increasing due to the aging of the infrastructure caused by the increase in industrial development and the expansion of citi...

Towards ML-Based Diagnostics of Laser-Plasma Interactions.

Sensors (Basel, Switzerland)
The power of machine learning (ML) in feature identification can be harnessed for determining quantities in experiments that are difficult to measure directly. However, if an ML model is trained on simulated data, rather than experimental results, th...

Prediction of In Vivo Laser-Induced Thermal Damage with Hyperspectral Imaging Using Deep Learning.

Sensors (Basel, Switzerland)
Thermal ablation is an acceptable alternative treatment for primary liver cancer, of which laser ablation (LA) is one of the least invasive approaches, especially for tumors in high-risk locations. Precise control of the LA effect is required to safe...

Real-Time Detection of Non-Stationary Objects Using Intensity Data in Automotive LiDAR SLAM.

Sensors (Basel, Switzerland)
This article aims at demonstrating the feasibility of modern deep learning techniques for the real-time detection of non-stationary objects in point clouds obtained from 3-D light detecting and ranging (LiDAR) sensors. The motion segmentation task is...

Graph Attention Feature Fusion Network for ALS Point Cloud Classification.

Sensors (Basel, Switzerland)
Classification is a fundamental task for airborne laser scanning (ALS) point cloud processing and applications. This task is challenging due to outdoor scenes with high complexity and point clouds with irregular distribution. Many existing methods ba...

The Effect of Synergistic Approaches of Features and Ensemble Learning Algorith on Aboveground Biomass Estimation of Natural Secondary Forests Based on ALS and Landsat 8.

Sensors (Basel, Switzerland)
Although the combination of Airborne Laser Scanning (ALS) data and optical imagery and machine learning algorithms were proved to improve the estimation of aboveground biomass (AGB), the synergistic approaches of different data and ensemble learning ...

Simultaneous Burr and Cut Interruption Detection during Laser Cutting with Neural Networks.

Sensors (Basel, Switzerland)
In this contribution, we compare basic neural networks with convolutional neural networks for cut failure classification during fiber laser cutting. The experiments are performed by cutting thin electrical sheets with a 500 W single-mode fiber laser ...

A Novel Approach to Automated 3D Spalling Defects Inspection in Railway Tunnel Linings Using Laser Intensity and Depth Information.

Sensors (Basel, Switzerland)
The detection of concrete spalling is critical for tunnel inspectors to assess structural risks and guarantee the daily operation of the railway tunnel. However, traditional spalling detection methods mostly rely on visual inspection or camera images...