Results 71 to 80 of about 234,090 (282)
International Journal of Interactive Multimedia and Artificial Intelligence, 2018 Neural network is widely used for image classification problems, and is proven to be effective with high successful rate. However one of its main challenges is the significant amount of time it takes to train the network.
Azizah Suliman, Batyrkhan Omarov
doaj +3 more sources
Modeling Breast Cancer Using Data Mining Methods
مجله انفورماتیک سلامت و زیست پزشکی, 2018 Introduction: Breast cancer is the most common form of cancer in women. Breast cancer detection is considered as one of the most important issues in medical science.
Parvaneh Dehghan +4 more
doaj
A Hierarchical Emotion Regulated Sensorimotor Model: Case Studies
, 2016 Inspired by the hierarchical cognitive architecture and the perception-action model (PAM), we propose that the internal status acts as a kind of common-coding representation which affects, mediates and even regulates the sensorimotor behaviours.
[No Value], IEEE +5 more
core +1 more source
Bayesian Perceptron: Towards fully Bayesian Neural Networks [PDF]
2020 59th IEEE Conference on Decision and Control (CDC), 2020 Accepted for publication at the 59th IEEE Conference on Decision and Control (CDC) 2020.
openaire +2 more sources
Flexible Sensor‐Based Human–Machine Interfaces with AI Integration for Medical Robotics
Advanced Robotics Research, EarlyView.This review explores how flexible sensing technology and artificial intelligence (AI) significantly enhance human–machine interfaces in medical robotics. It highlights key sensing mechanisms, AI‐driven advancements, and applications in prosthetics, exoskeletons, and surgical robotics.
Yuxiao Wang +5 more
wiley +1 more source
Advanced Robotics Research, EarlyView.An introduction for multidrive and environment‐adaptive micro/nanorobotics: design and fabrication strategies, intelligent actuation, and their applications. Various intelligent actuation approaches—magnetic, acoustic, optical, chemical, and biological—can be synergistically designed to enhance flexibility and adaptive behavior for precision medicine ...
Aiqing Ma +10 more
wiley +1 more source
Nonlinear modeling with confidence estimation using Bayesian neural networks
Electronic Journal of Structural Engineering, 2004 There is a growing interest in the use of neural networks in civil engineering to model complicated nonlinearity problems. A recent enhancement to the conventional back-propagation neural network algorithm is the adoption of a Bayesian inference ...
A.T.C. Goh, C.G. Chua
doaj
BOCK : Bayesian Optimization with Cylindrical Kernels [PDF]
, 2018 A major challenge in Bayesian Optimization is the boundary issue (Swersky, 2017) where an algorithm spends too many evaluations near the boundary of its search space.
Gavves, Efstratios +2 more
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Bayesian Neural Network Ensembles
, 2018 Ensembles of neural networks (NNs) have long been used to estimate predictive uncertainty; a small number of NNs are trained from different initialisations and sometimes on differing versions of the dataset. The variance of the ensemble's predictions is interpreted as its epistemic uncertainty.
Pearce, Tim, Zaki, Mohamed, Neely, Andy
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Hard‐Magnetic Soft Millirobots in Underactuated Systems
Advanced Robotics Research, EarlyView.This review provides a comprehensive overview of hard‐magnetic soft millirobots in underactuated systems. It examines key advances in structural design, physics‐informed modeling, and control strategies, while highlighting the interplay among these domains.
Qiong Wang +4 more
wiley +1 more source