AI Medical Compendium Topic

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Recognition, Psychology

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Improving Inertial Sensor-Based Activity Recognition in Neurological Populations.

Sensors (Basel, Switzerland)
Inertial sensor-based human activity recognition (HAR) has a range of healthcare applications as it can indicate the overall health status or functional capabilities of people with impaired mobility. Typically, artificial intelligence models achieve ...

Resolving the neural mechanism of core object recognition in space and time: A computational approach.

Neuroscience research
The underlying mechanism of object recognition- a fundamental brain ability- has been investigated in various studies. However, balancing between the speed and accuracy of recognition is less explored. Most of the computational models of object recog...

Automatic Recognition of Road Damage Based on Lightweight Attentional Convolutional Neural Network.

Sensors (Basel, Switzerland)
An efficient road damage detection system can reduce the risk of road defects to motorists and road maintenance costs to traffic management authorities, for which a lightweight end-to-end road damage detection network is proposed in this paper, aimin...

LPAI-A Complete AIoT Framework Based on LPWAN Applicable to Acoustic Scene Classification Scenarios.

Sensors (Basel, Switzerland)
Deploying artificial intelligence on edge nodes of Low-Power Wide Area Networks can significantly reduce network transmission volumes, event response latency, and overall network power consumption. However, the edge nodes in LPWAN bear limited comput...

Position-Aware Participation-Contributed Temporal Dynamic Model for Group Activity Recognition.

IEEE transactions on neural networks and learning systems
Group activity recognition (GAR) aiming at understanding the behavior of a group of people in a video clip has received increasing attention recently. Nevertheless, most of the existing solutions ignore that not all the persons contribute to the grou...

Applying Self-Supervised Representation Learning for Emotion Recognition Using Physiological Signals.

Sensors (Basel, Switzerland)
The use of machine learning (ML) techniques in affective computing applications focuses on improving the user experience in emotion recognition. The collection of input data (e.g., physiological signals), together with expert annotations are part of ...

MSFF-Net: Multi-Stream Feature Fusion Network for surface electromyography gesture recognition.

PloS one
In the field of surface electromyography (sEMG) gesture recognition, how to improve recognition accuracy has been a research hotspot. The rapid development of deep learning provides a new solution to this problem. At present, the main applications of...

Arabic Syntactic Diacritics Restoration Using BERT Models.

Computational intelligence and neuroscience
The Arabic syntactic diacritics restoration problem is often solved using long short-term memory (LSTM) networks. Handcrafted features are used to augment these LSTM networks or taggers to improve performance. A transformer-based machine learning tec...

Developmental Network-2: The Autonomous Generation of Optimal Internal-Representation Hierarchy.

IEEE transactions on neural networks and learning systems
It is very challenging for machine learning methods to reach the goal of general-purpose learning since there are so many complicated situations in different tasks. The learning methods need to generate flexible internal representations for all scena...

Improved Feature Parameter Extraction from Speech Signals Using Machine Learning Algorithm.

Sensors (Basel, Switzerland)
Speech recognition refers to the capability of software or hardware to receive a speech signal, identify the speaker's features in the speech signal, and recognize the speaker thereafter. In general, the speech recognition process involves three main...