AIMC Topic: Neural Networks, Computer

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Novel optimal trajectory tracking for nonlinear affine systems with an advanced critic learning structure.

Neural networks : the official journal of the International Neural Network Society
In this paper, a critic learning structure based on the novel utility function is developed to solve the optimal tracking control problem with the discount factor of affine nonlinear systems. The utility function is defined as the quadratic form of t...

A new brain tumor diagnostic model: Selection of textural feature extraction algorithms and convolution neural network features with optimization algorithms.

Computers in biology and medicine
Brain tumors are one of the most dangerous diseases that affect human health and maybe result in death. Detection of brain tumors can be made by using biopsy. However, this is an invasive procedure. It is an extremely dangerous procedure because it c...

Leveraging ShuffleNet transfer learning to enhance handwritten character recognition.

Gene expression patterns : GEP
Handwritten character recognition has continually been a fascinating field of study in pattern recognition due to its numerous real-life applications, such as the reading tools for blind people and the reading tools for handwritten bank cheques. Ther...

On the Tuning of the Computation Capability of Spiking Neural Membrane Systems with Communication on Request.

International journal of neural systems
Spiking neural P systems (abbreviated as SNP systems) are models of computation that mimic the behavior of biological neurons. The spiking neural P systems with communication on request (abbreviated as SNQP systems) are a recently developed class of ...

Reconstructing Superquadrics from Intensity and Color Images.

Sensors (Basel, Switzerland)
The task of reconstructing 3D scenes based on visual data represents a longstanding problem in computer vision. Common reconstruction approaches rely on the use of multiple volumetric primitives to describe complex objects. Superquadrics (a class of ...

Well Performance Classification and Prediction: Deep Learning and Machine Learning Long Term Regression Experiments on Oil, Gas, and Water Production.

Sensors (Basel, Switzerland)
In the oil and gas industries, predicting and classifying oil and gas production for hydrocarbon wells is difficult. Most oil and gas companies use reservoir simulation software to predict future oil and gas production and devise optimum field develo...

A RUL Estimation System from Clustered Run-to-Failure Degradation Signals.

Sensors (Basel, Switzerland)
The prognostics and health management disciplines provide an efficient solution to improve a system's durability, taking advantage of its lifespan in functionality before a failure appears. Prognostics are performed to estimate the system or subsyste...

A Novel Hybrid Algorithm for the Forward Kinematics Problem of 6 DOF Based on Neural Networks.

Sensors (Basel, Switzerland)
The closed kinematic structure of Gough-Stewart platforms causes the kinematic control problem, particularly forward kinematics. In the traditional hybrid algorithm (backpropagation neural network and Newton-Raphson), it is difficult for the neural n...

3D Convolutional Neural Network Framework with Deep Learning for Nuclear Medicine.

Scanning
Though artificial intelligence (AI) has been used in nuclear medicine for more than 50 years, more progress has been made in deep learning (DL) and machine learning (ML), which have driven the development of new AI abilities in the field. ANNs are us...

Cartoon-Style Image Rendering Transfer Based on Neural Networks.

Computational intelligence and neuroscience
Cartoon rendering of images is a challenging nonphotorealistic image rendering task, which aims to transform real photos into cartoon-style nonphotorealistic images while preserving the semantic content and texture details of the original photos. Bas...