Instruct: Given the title of a scientific paper, retrieve paper titles that are cited by the given paper.
Query: A New Convolutional Neural Network-Based Data-Driven Fault Diagnosis Method
Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks
Stacked Sparse Autoencoder-Based Deep Network for Fault Diagnosis of Rotating Machinery
An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox
Reconstruction independent component analysis-based methods for intelligent fault diagnosis
Artificial neural network approach for fault detection in rotary system
A data mining approach for fault diagnosis: An application of anomaly detection algorithm
Deep Learning-Based Crack Damage Detection Using Convolutional Neural Networks
Model-based fault diagnosis in electric drives using machine learning
Deep Model Based Domain Adaptation for Fault Diagnosis
An Imbalance Modified Deep Neural Network With Dynamical Incremental Learning for Chemical Fault Diagnosis
A Deep Learning Approach for Fault Diagnosis of Induction Motors in Manufacturing
An Intelligent Fault Diagnosis Method Using Unsupervised Feature Learning Towards Mechanical Big Data
One-class support vector machines - an application in machine fault detection and classification
Neural-network-based motor rolling bearing fault diagnosis
Software Defect Prediction via Convolutional Neural Network
Robust Model-Based Fault Diagnosis for Dynamic Systems
Deep Recurrent and Convolutional Networks for Accelerated Fault Tolerant Adaptive Flight Control Under Severe Failures
Accelerated Artificial Neural Networks on FPGA for fault detection in automotive systems
On Practical Aspects of Using RNNs for Fault Detection in Sparsely-Labeled Multi-sensor Time Series
Food Detection and Recognition Using Convolutional Neural Network
MEASURING ERP SYSTEM SUCCESS: A RESPECIFICATION OF THE DELONE AND MCLEAN’S IS SUCCESS MODEL
SURE-based optimization for adaptive sampling and reconstruction
Animated People Textures
Visualizing and Understanding Convolutional Networks
Enhancement of Residual Echo for Robust Acoustic Echo Cancellation