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Found 10 papers, 3 papers with code
3D-CSAD: Untrained 3D Anomaly Detection for Complex Manufacturing Surfaces
To address these challenges, we propose a novel untrained anomaly detection method based on 3D point cloud data for complex manufacturing parts, which can achieve accurate anomaly detection in a single sample without training data.
DeepFunction: Deep Metric Learning-based Imbalanced Classification for Diagnosing Threaded Pipe Connection Defects using Functional Data
To classify the defect samples based on imbalanced, multichannel, and incomplete functional data is very important but challenging.
Tensor-based process control and monitoring for semiconductor manufacturing with unstable disturbances
This paper proposes a novel process control and monitoring method for the complex structure of high-dimensional image-based overlay errors (modeled in tensor form), which are collected in semiconductor manufacturing processes.
Ano-SuPs: Multi-size anomaly detection for manufactured products by identifying suspected patches
Image-based systems have gained popularity owing to their capacity to provide rich manufacturing status information, low implementation costs and high acquisition rates.
MFRL-BI: Design of a Model-free Reinforcement Learning Process Control Scheme by Using Bayesian Inference
Design of process control scheme is critical for quality assurance to reduce variations in manufacturing systems.
Reinforcement Learning for Process Control with Application in Semiconductor Manufacturing
Process control is widely discussed in the manufacturing process, especially for semiconductor manufacturing.
Temporal-Relational Hypergraph Tri-Attention Networks for Stock Trend Prediction
Extensive experiments on real-world data demonstrate the effectiveness of our approach.
SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud based Place Recognition
We tackle the problem of place recognition from point cloud data and introduce a self-attention and orientation encoding network (SOE-Net) that fully explores the relationship between points and incorporates long-range context into point-wise local descriptors.
Ranked #5 on
3D Place Recognition
on Oxford RobotCar Dataset
(AR@1% metric)
DH3D: Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DoF Relocalization
We generate the global descriptor by directly aggregating the learned local descriptors with an effective attention mechanism.
Ranked #7 on
3D Place Recognition
on Oxford RobotCar Dataset
Object Tracking in Hyperspectral Videos with Convolutional Features and Kernelized Correlation Filter
Target tracking in hyperspectral videos is a new research topic.
