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Quality monitoring in multistage manufacturing systems by using machine learning techniques
Manufacturing and production processes have become more complicated and usually
consist of multiple stages to meet customers' requirements. This poses big challenges for …
consist of multiple stages to meet customers' requirements. This poses big challenges for …
MI-MOTE: Multiple imputation-based minority oversampling technique for imbalanced and incomplete data classification
Class imbalance and data incompleteness problems occur simultaneously in many real-
world classification datasets, which negatively affects the training of classifiers. Given an …
world classification datasets, which negatively affects the training of classifiers. Given an …
Unsupervised pre-training of imbalanced data for identification of wafer map defect patterns
Visual defect inspection and classification are significant steps of most manufacturing
processes in the semiconductor and electronics industries. Known and unknown defects on …
processes in the semiconductor and electronics industries. Known and unknown defects on …
Machine learning-based techniques for fault diagnosis in the semiconductor manufacturing process: a comparative study
Industries are going through the fourth industrial revolution (Industry 4.0), where
technologies like the Industrial Internet of things, big data analytics, and machine learning …
technologies like the Industrial Internet of things, big data analytics, and machine learning …
Semi-GAN: An improved GAN-based missing data imputation method for the semiconductor industry
SY Lee, TP Connerton, YW Lee, D Kim, D Kim… - Ieee …, 2022 - ieeexplore.ieee.org
Complete data are required for the operation, maintenance, and detection of faults in
semiconductor equipment. Missing data occur frequently because of defects such as sensor …
semiconductor equipment. Missing data occur frequently because of defects such as sensor …
Artificial immune system for fault detection and classification of semiconductor equipment
Semiconductor manufacturing comprises hundreds of consecutive unit processes. A single
misprocess could jeopardize the whole manufacturing process. In current manufacturing …
misprocess could jeopardize the whole manufacturing process. In current manufacturing …
Interpretation of a deep analysis of speech imagery features extracted by a capsule neural network
Speech imagery has been successfully employed in develo** Brain–Computer Interfaces
because it is a novel mental strategy that generates brain activity more intuitively than …
because it is a novel mental strategy that generates brain activity more intuitively than …
Pruning Quantized Unsupervised Meta-Learning DegradingNet Solution for Industrial Equipment and Semiconductor Process Anomaly Detection and Prediction
Machine-and deep-learning methods are used for industrial applications in prognostics and
health management (PHM) for semiconductor processing and equipment anomaly detection …
health management (PHM) for semiconductor processing and equipment anomaly detection …
A new data analytics framework emphasising preprocessing of data to generate insights into complex manufacturing systems
Recent emphasis has been placed on improving the processes in manufacturing by
employing early detection or fault prediction within production lines. Whilst companies are …
employing early detection or fault prediction within production lines. Whilst companies are …
Particle swarm optimization based deep learning ensemble for manufacturing processes
Faults detection in semiconductor manufacturing processes is a challenging research
problem because the manufacturing processes are characterized by hundreds of different …
problem because the manufacturing processes are characterized by hundreds of different …