AIMC Topic: Recognition, Psychology

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Comparing Handcrafted Features and Deep Neural Representations for Domain Generalization in Human Activity Recognition.

Sensors (Basel, Switzerland)
Human Activity Recognition (HAR) has been studied extensively, yet current approaches are not capable of generalizing across different domains (i.e., subjects, devices, or datasets) with acceptable performance. This lack of generalization hinders the...

Fast Temporal Graph Convolutional Model for Skeleton-Based Action Recognition.

Sensors (Basel, Switzerland)
Human action recognition has a wide range of applications, including Ambient Intelligence systems and user assistance. Starting from the recognized actions performed by the user, a better human-computer interaction can be achieved, and improved assis...

Aeroengine Working Condition Recognition Based on MsCNN-BiLSTM.

Sensors (Basel, Switzerland)
Aeroengine working condition recognition is a pivotal step in engine fault diagnosis. Currently, most research on aeroengine condition recognition focuses on the stable condition. To identify the aeroengine working conditions including transition con...

A Hierarchical Ensemble Deep Learning Activity Recognition Approach with Wearable Sensors Based on Focal Loss.

International journal of environmental research and public health
Abnormal activity in daily life is a relatively common symptom of chronic diseases, such as dementia. There will probably be a variety of repetitive activities in dementia patients' daily life, such as repeated handling of objects and repeated packin...

Real-Time and Efficient Multi-Scale Traffic Sign Detection Method for Driverless Cars.

Sensors (Basel, Switzerland)
Traffic signs detection and recognition is an essential and challenging task for driverless cars. However, the detection of traffic signs in most scenarios belongs to small target detection, and most existing object detection methods show poor perfor...

A pre-trained BERT for Korean medical natural language processing.

Scientific reports
With advances in deep learning and natural language processing (NLP), the analysis of medical texts is becoming increasingly important. Nonetheless, despite the importance of processing medical texts, no research on Korean medical-specific language m...

Risky-Driving-Image Recognition Based on Visual Attention Mechanism and Deep Learning.

Sensors (Basel, Switzerland)
Risky driving behavior seriously affects the driver's ability to react, execute and judge, which is one of the major causes of traffic accidents. The timely and accurate identification of the driving status of drivers is particularly important, since...

Automatic Swimming Activity Recognition and Lap Time Assessment Based on a Single IMU: A Deep Learning Approach.

Sensors (Basel, Switzerland)
This study presents a deep learning model devoted to the analysis of swimming using a single Inertial Measurement Unit (IMU) attached to the sacrum. Gyroscope and accelerometer data were collected from 35 swimmers with various expertise levels during...

Lead federated neuromorphic learning for wireless edge artificial intelligence.

Nature communications
In order to realize the full potential of wireless edge artificial intelligence (AI), very large and diverse datasets will often be required for energy-demanding model training on resource-constrained edge devices. This paper proposes a lead federate...

Cultural and Creative Product Design and Image Recognition Based on the Convolutional Neural Network Model.

Computational intelligence and neuroscience
The development in technology has resulted in the utilization of artificial intelligence systems in various fields. In this research, we are going to study cultural and creative product design and image recognition based on a convolutional neural net...