AIMC Topic: Recognition, Psychology

Clear Filters Showing 61 to 70 of 279 articles

The Effects of Social Presence and Familiarity on Children-Robot Interactions.

Sensors (Basel, Switzerland)
In children-robot interactions, an impression of a robot's "social presence" (i.e., an interactive agent that feels like a person) links positively to an improved relationship with the robot. However, building relationships takes many exposures, and ...

EXPLORE: a novel deep learning-based analysis method for exploration behaviour in object recognition tests.

Scientific reports
Object recognition tests are widely used in neuroscience to assess memory function in rodents. Despite the experimental simplicity of the task, the interpretation of behavioural features that are counted as object exploration can be complicated. Thus...

Optimization Algorithm of Moving Object Detection Using Multiscale Pyramid Convolutional Neural Networks.

Computational intelligence and neuroscience
Object detection and recognition is a very important topic with significant research value. This research develops an optimised model of moving target identification based on CNN to address the issues of insufficient positioning information and low t...

A New Deep-Learning Method for Human Activity Recognition.

Sensors (Basel, Switzerland)
Currently, three-dimensional convolutional neural networks (3DCNNs) are a popular approach in the field of human activity recognition. However, due to the variety of methods used for human activity recognition, we propose a new deep-learning model in...

Deep learning-based open set multi-source domain adaptation with complementary transferability metric for mechanical fault diagnosis.

Neural networks : the official journal of the International Neural Network Society
Intelligent fault diagnosis aims to build robust mechanical condition recognition models with limited dataset. At this stage, fault diagnosis faces two practical challenges: (1) the variability of mechanical working conditions makes the collected dat...

Rethinking Breast Cancer Diagnosis through Deep Learning Based Image Recognition.

Sensors (Basel, Switzerland)
This paper explored techniques for diagnosing breast cancer using deep learning based medical image recognition. X-ray (Mammography) images, ultrasound images, and histopathology images are used to improve the accuracy of the process by diagnosing br...

sEMG-Based Hand Gesture Recognition Using Binarized Neural Network.

Sensors (Basel, Switzerland)
Recently, human-machine interfaces (HMI) that make life convenient have been studied in many fields. In particular, a hand gesture recognition (HGR) system, which can be implemented as a wearable system, has the advantage that users can easily and in...

Towards a Safe Human-Robot Collaboration Using Information on Human Worker Activity.

Sensors (Basel, Switzerland)
Most industrial workplaces involving robots and other apparatus operate behind the fences to remove defects, hazards, or casualties. Recent advancements in machine learning can enable robots to co-operate with human co-workers while retaining safety,...

Fault Identification and Localization of a Time-Frequency Domain Joint Impedance Spectrum of Cables Based on Deep Belief Networks.

Sensors (Basel, Switzerland)
To improve the accuracy of shallow neural networks in processing complex signals and cable fault diagnosis, and to overcome the shortage of manual dependency and cable fault feature extraction, a deep learning method is introduced, and a time-frequen...

An AI-Inspired Spatio-Temporal Neural Network for EEG-Based Emotional Status.

Sensors (Basel, Switzerland)
The accurate identification of the human emotional status is crucial for an efficient human-robot interaction (HRI). As such, we have witnessed extensive research efforts made in developing robust and accurate brain-computer interfacing models based ...