AIMC Topic: Normal Distribution

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Enhanced Classification of Dog Activities with Quaternion-Based Fusion Approach on High-Dimensional Raw Data from Wearable Sensors.

Sensors (Basel, Switzerland) Dec 4, 2022
The employment of machine learning algorithms to the data provided by wearable movement sensors is one of the most common methods to detect pets' behaviors and monitor their well-being. However, defining features that lead to highly accurate behavior...
Machine Learning Algorithms Animals Support Vector Machine Bayes Theorem Dogs Normal Distribution
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Sensor Fusion for Social Navigation on a Mobile Robot Based on Fast Marching Square and Gaussian Mixture Model.

Sensors (Basel, Switzerland) Nov 11, 2022
Mobile robot navigation has been studied for a long time, and it is nowadays widely used in multiple applications. However, it is traditionally focused on two-dimensional geometric characteristics of the environments. There are situations in which ro...
Humans Robotics Normal Distribution
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Prior Guided Transformer for Accurate Radiology Reports Generation.

IEEE journal of biomedical and health informatics Nov 10, 2022
In this paper, we propose a prior guided transformer for accurate radiology reports generation. In the encoder part, a radiograph is firstly represented by a set of patch features, which is obtained through a convolutional neural network and a tradit...
Humans Neural Networks, Computer Radiography Radiology Normal Distribution
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Multistability of Switched Neural Networks With Gaussian Activation Functions Under State-Dependent Switching.

IEEE transactions on neural networks and learning systems Oct 27, 2022
This article presents theoretical results on the multistability of switched neural networks with Gaussian activation functions under state-dependent switching. It is shown herein that the number and location of the equilibrium points of the switched ...
Neural Networks, Computer Algorithms Computer Simulation Neurons Normal Distribution
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Tropical support vector machines: Evaluations and extension to function spaces.

Neural networks : the official journal of the International Neural Network Society Oct 13, 2022
Support Vector Machines (SVMs) are one of the most popular supervised learning models to classify using a hyperplane in an Euclidean space. Similar to SVMs, tropical SVMs classify data points using a tropical hyperplane under the tropical metric with...
Forecasting Support Vector Machine Normal Distribution
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Deep residual neural-network-based robot joint fault diagnosis method.

Scientific reports Oct 13, 2022
A data driven method-based robot joint fault diagnosis method using deep residual neural network (DRNN) is proposed, where Resnet-based fault diagnosis method is introduced. The proposed method mainly deals with kinds of fault types, such as gain err...
Neural Networks, Computer Computer Simulation Support Vector Machine Robotics Normal Distribution
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GPCA: A Probabilistic Framework for Gaussian Process Embedded Channel Attention.

IEEE transactions on pattern analysis and machine intelligence Oct 4, 2022
Channel attention mechanisms have been commonly applied in many visual tasks for effective performance improvement. It is able to reinforce the informative channels as well as to suppress the useless channels. Recently, different channel attention mo...
Neural Networks, Computer Algorithms Normal Distribution
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Kirigami-Inspired Programmable Soft Magnetoresponsive Actuators with Versatile Morphing Modes.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Sep 30, 2022
Untethered soft magnetoresponsive actuators (SMRAs), which can realize rapid shape transformation, have attracted widespread attention for their strategic applications in exploration, transportation, and minimally invasive medicine. It remains a chal...
Robotics Normal Distribution Finite Element Analysis
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Uncertainty Estimation Using Variational Mixture of Gaussians Capsule Network for Health Image Classification.

Computational intelligence and neuroscience Sep 30, 2022
Capsule Networks have shown great promise in image recognition due to their ability to recognize the pose, texture, and deformation of objects and object parts. However, the majority of the existing capsule networks are deterministic with limited abi...
Neural Networks, Computer Reproducibility of Results Bayes Theorem Normal Distribution Uncertainty
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Time series (re)sampling using Generative Adversarial Networks.

Neural networks : the official journal of the International Neural Network Society Sep 23, 2022
We propose a novel bootstrap procedure for time series data based on Generative Adversarial networks (GANs). We show that the dynamics of common stationary time series processes can be learned by GANs and demonstrate that GANs trained on a single sam...
Neural Networks, Computer Learning Time Factors Image Processing, Computer-Assisted Normal Distribution
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