AIMC Topic: Pattern Recognition, Automated

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Intelligent recognition of human activities using deep learning techniques.

PloS one
Recognition of Human Actions (HAR) Portrays a crucial significance in various applications due to its ability for analyzing behaviour of humans within videos. This research investigates HAR in Red, Green, and Blue, or RGB videos using frameworks for ...

Repetitive training enhances the pattern recognition capability of cultured neural networks.

PLoS computational biology
Cultured neural networks in vitro have demonstrated the biocomputing capability to recognize patterns. However, the underlying mechanisms behind information processing and pattern recognition remain less understood. Here, we developed an in vitro neu...

Deep learning-based recognition model of football player's technical action behavior using PCA-LBP algorithm.

Scientific reports
Football is a sport that requires sportsmen to have both physical strength and physical features. It must consider the distinctions between individuals and then provide targeted training. Football players can perform better on the field with targeted...

sEMG-Based Gesture Recognition via Multi-Feature Fusion Network.

IEEE journal of biomedical and health informatics
The sparse surface electromyography-based gesture recognition suffers from the problems of feature information not richness and poor generalization to small sample data. Therefore, a multi-feature fusion network (MFF-Net) model is proposed in this pa...

An Efficient Graph Learning System for Emotion Recognition Inspired by the Cognitive Prior Graph of EEG Brain Network.

IEEE transactions on neural networks and learning systems
Benefiting from the high-temporal resolution of electroencephalogram (EEG), EEG-based emotion recognition has become one of the hotspots of affective computing. For EEG-based emotion recognition systems, it is crucial to utilize state-of-the-art lear...

Robust Sensory Information Reconstruction and Classification With Augmented Spikes.

IEEE transactions on neural networks and learning systems
Sensory information recognition is primarily processed through the ventral and dorsal visual pathways in the primate brain visual system, which exhibits layered feature representations bearing a strong resemblance to convolutional neural networks (CN...

IoT powered RNN for improved human activity recognition with enhanced localization and classification.

Scientific reports
Human activity recognition (HAR) and localization are green research areas of the modern era that are being propped up by smart devices. But the data acquired from the sensors embedded in smart devices, contain plenty of noise that makes it indispens...

DT-Transformer: A Text-Tactile Fusion Network for Object Recognition.

IEEE transactions on haptics
Humans rely on multiple senses to understand their surroundings, and so do robots. Current research in haptic object classification focuses on visual-haptic methods, but faces limitations in performance and dataset size. Unlike images, text does not ...

Object Recognition Using Shape and Texture Tactile Information: A Fusion Network Based on Data Augmentation and Attention Mechanism.

IEEE transactions on haptics
Currently, most tactile-based object recognition algorithms focus on single shape or texture recognition. However, these single attribute-based recognition methods perform poorly when dealing with objects with similar shape or texture characteristics...

Kinetic Pattern Recognition in Home-Based Knee Rehabilitation Using Machine Learning Clustering Methods on the Slider Digital Physiotherapy Device: Prospective Observational Study.

JMIR formative research
BACKGROUND: Recent advancements in rehabilitation sciences have progressively used computational techniques to improve diagnostic and treatment approaches. However, the analysis of high-dimensional, time-dependent data continues to pose a significant...