AIMC Topic: Recognition, Psychology

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Multi-LiDAR Mapping for Scene Segmentation in Indoor Environments for Mobile Robots.

Sensors (Basel, Switzerland)
Nowadays, most mobile robot applications use two-dimensional LiDAR for indoor mapping, navigation, and low-level scene segmentation. However, single data type maps are not enough in a six degree of freedom world. Multi-LiDAR sensor fusion increments ...

A Novel CNN-based Bi-LSTM parallel model with attention mechanism for human activity recognition with noisy data.

Scientific reports
Boosted by mobile communication technologies, Human Activity Recognition (HAR) based on smartphones has attracted more and more attentions of researchers. One of the main challenges is the classification time and accuracy in processing long-time depe...

Event-Driven Intrinsic Plasticity for Spiking Convolutional Neural Networks.

IEEE transactions on neural networks and learning systems
The biologically discovered intrinsic plasticity (IP) learning rule, which changes the intrinsic excitability of an individual neuron by adaptively turning the firing threshold, has been shown to be crucial for efficient information processing. Howev...

Contrastive Adversarial Domain Adaptation Networks for Speaker Recognition.

IEEE transactions on neural networks and learning systems
Domain adaptation aims to reduce the mismatch between the source and target domains. A domain adversarial network (DAN) has been recently proposed to incorporate adversarial learning into deep neural networks to create a domain-invariant space. Howev...

Hypertuned Deep Convolutional Neural Network for Sign Language Recognition.

Computational intelligence and neuroscience
Sign language plays a pivotal role in the lives of impaired people having speaking and hearing disabilities. They can convey messages using hand gesture movements. American Sign Language (ASL) recognition is challenging due to the increasing intra-cl...

Three-Level Distributed Real-Time Monitoring of Construction near Underground Infrastructure Using a Combined Intelligent Method.

Sensors (Basel, Switzerland)
With the rapid development of underground infrastructure and the uncertainty of its location, the possibility of damage due to nearby construction has increased. Thus, for the early warning of dangerous construction behaviors around underground facil...

Multihydrophone Fusion Network for Modulation Recognition.

Sensors (Basel, Switzerland)
Deep learning (DL)-based modulation recognition methods of underwater acoustic communication signals are mostly applied to a single hydrophone reception scenario. In this paper, we propose a novel end-to-end multihydrophone fusion network (MHFNet) fo...

A Comprehensive Review of Recent Deep Learning Techniques for Human Activity Recognition.

Computational intelligence and neuroscience
Human action recognition is an important field in computer vision that has attracted remarkable attention from researchers. This survey aims to provide a comprehensive overview of recent human action recognition approaches based on deep learning usin...

An Automated Image-Based Multivariant Concrete Defect Recognition Using a Convolutional Neural Network with an Integrated Pooling Module.

Sensors (Basel, Switzerland)
Buildings and infrastructure in congested metropolitan areas are continuously deteriorating. Various structural flaws such as surface cracks, spalling, delamination, and other defects are found, and keep on progressing. Traditionally, the assessment ...

Emotion Recognition from Physiological Channels Using Graph Neural Network.

Sensors (Basel, Switzerland)
In recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presente...