AIMC Topic: Motion

Clear Filters Showing 311 to 320 of 879 articles

Artificial Neural Network Approach to Guarantee the Positioning Accuracy of Moving Robots by Using the Integration of IMU/UWB with Motion Capture System Data Fusion.

Sensors (Basel, Switzerland)
This study presents an effective artificial neural network (ANN) approach to combine measurements from inertial measurement units (IMUs) and time-of-flight (TOF) measurements from an ultra-wideband (UWB) system with OptiTrack Motion Capture System (O...

Discrete Missing Data Imputation Using Multilayer Perceptron and Momentum Gradient Descent.

Sensors (Basel, Switzerland)
Data are a strategic resource for industrial production, and an efficient data-mining process will increase productivity. However, there exist many missing values in data collected in real life due to various problems. Because the missing data may re...

A time motion study of manual versus artificial intelligence methods for wound assessment.

PloS one
OBJECTIVES: This time-motion study explored the amount of time clinicians spent on wound assessments in a real-world environment using wound assessment digital application utilizing Artificial Intelligence (AI) vs. manual methods. The study also aime...

Estimating heading from optic flow: Comparing deep learning network and human performance.

Neural networks : the official journal of the International Neural Network Society
Convolutional neural networks (CNNs) have made significant advances over the past decade with visual recognition, matching or exceeding human performance on certain tasks. Visual recognition is subserved by the ventral stream of the visual system, wh...

Design of Moving Target Detection System Using Lightweight Deep Learning Model and Its Impact on the Development of Sports Industry.

Computational intelligence and neuroscience
The intelligent tracking and detection of athletes' actions and the improvement of action standardization are of great practical significance to reducing the injury caused by sports in the sports industry. For the problems of nonstandard movement and...

Milli-scale cellular robots that can reconfigure morphologies and behaviors simultaneously.

Nature communications
Modular robot that can reconfigure architectures and functions has advantages in unpredicted environment and task. However, the construction of modular robot at small-scale remains a challenge since the lack of reliable docking and detaching strategi...

QMEDNet: A quaternion-based multi-order differential encoder-decoder model for 3D human motion prediction.

Neural networks : the official journal of the International Neural Network Society
In order to deal with the sequence information in the task of 3D human motion prediction effectively, many previous methods seek to predict the motion state of the next moment using the traditional recurrent neural network in Euclidean space. However...

Development of Smartphone Application for Markerless Three-Dimensional Motion Capture Based on Deep Learning Model.

Sensors (Basel, Switzerland)
To quantitatively assess pathological gait, we developed a novel smartphone application for full-body human motion tracking in real time from markerless video-based images using a smartphone monocular camera and deep learning. As training data for de...

Application of Improved VMD-LSTM Model in Sports Artificial Intelligence.

Computational intelligence and neuroscience
In recent years, with the rapid development of a new generation of artificial intelligence technology, how to deeply apply artificial intelligence technology to physical education and break through the limitations of time-space scenarios and knowledg...

Fully body visual self-modeling of robot morphologies.

Science robotics
Internal computational models of physical bodies are fundamental to the ability of robots and animals alike to plan and control their actions. These "self-models" allow robots to consider outcomes of multiple possible future actions without trying th...