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Pattern Recognition, Automated

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An efficient framework based on local multi-representatives and noise-robust synthetic example generation for self-labeled semi-supervised classification.

Neural networks : the official journal of the International Neural Network Society
While self-labeled methods can exploit unlabeled and labeled instances to train classifiers, they are also restricted by the labeled instance number and distribution. SEG-SSC, k-means-SSC, LC-SSC, and LCSEG-SSC are sophisticated solutions for overcom...

Real-Time On-Device Continual Learning Based on a Combined Nearest Class Mean and Replay Method for Smartphone Gesture Recognition.

Sensors (Basel, Switzerland)
Sensor-based gesture recognition on mobile devices is critical to human-computer interaction, enabling intuitive user input for various applications. However, current approaches often rely on server-based retraining whenever new gestures are introduc...

Multi-Label Zero-Shot Learning Via Contrastive Label-Based Attention.

International journal of neural systems
Multi-label zero-shot learning (ML-ZSL) strives to recognize all objects in an image, regardless of whether they are present in the training data. Recent methods incorporate an attention mechanism to locate labels in the image and generate class-spec...

DCTCNet: Sequency discrete cosine transform convolution network for visual recognition.

Neural networks : the official journal of the International Neural Network Society
The discrete cosine transform (DCT) has been widely used in computer vision tasks due to its ability of high compression ratio and high-quality visual presentation. However, conventional DCT is usually affected by the size of transform region and res...

Contrastive independent subspace analysis network for multi-view spatial information extraction.

Neural networks : the official journal of the International Neural Network Society
Multi-view classification integrates features from different views to optimize classification performance. Most of the existing works typically utilize semantic information to achieve view fusion but neglect the spatial information of data itself, wh...

PFENet: Towards precise feature extraction from sparse point cloud for 3D object detection.

Neural networks : the official journal of the International Neural Network Society
Accurate 3D point cloud object detection is crucially important for autonomous driving vehicles. The sparsity of point clouds in 3D scenes, especially for smaller targets like pedestrians and bicycles that contain fewer points, makes detection partic...

A discriminative multi-modal adaptation neural network model for video action recognition.

Neural networks : the official journal of the International Neural Network Society
Research on video-based understanding and learning has attracted widespread interest and has been adopted in various real applications, such as e-healthcare, action recognition, affective computing, to name a few. Amongst them, video-based action rec...

An adversarial transformer for anomalous lamb wave pattern detection.

Neural networks : the official journal of the International Neural Network Society
Lamb waves are widely used for defect detection in structural health monitoring, and various methods are developed for Lamb wave data analysis. This paper presents an unsupervised Adversarial Transformer model for anomalous Lamb wave pattern detectio...

Vision Sensor for Automatic Recognition of Human Activities via Hybrid Features and Multi-Class Support Vector Machine.

Sensors (Basel, Switzerland)
Over recent years, automated Human Activity Recognition (HAR) has been an area of concern for many researchers due to its widespread application in surveillance systems, healthcare environments, and many more. This has led researchers to develop cohe...

GSE: A global-local storage enhanced video object recognition model.

Neural networks : the official journal of the International Neural Network Society
The presence of substantial similarities and redundant information within video data limits the performance of video object recognition models. To address this issue, a Global-Local Storage Enhanced video object recognition model (GSE) is proposed in...