AIMC Topic: Algorithms

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Trajectory Optimization in Terms of Energy and Performance of an Industrial Robot in the Manufacturing Industry.

Sensors (Basel, Switzerland)
Currently, the high demand for new products in the automotive sector requires large investments in factories. The automotive industry is characterized by high automatization, largely achieved by manipulator robots capable of multitasking. This work p...

The effect of an artificial intelligence algorithm on chest X-ray interpretation of radiology residents.

The British journal of radiology
OBJECTIVE: Chest X-rays are the most commonly performed diagnostic examinations. An artificial intelligence (AI) system that evaluates the images fast and accurately help reducing workflow and management of the patients. An automated assistant may re...

Unified Analysis on the Global Dissipativity and Stability of Fractional-Order Multidimension-Valued Memristive Neural Networks With Time Delay.

IEEE transactions on neural networks and learning systems
The unified criteria are analyzed on the global dissipativity and stability for the delayed fractional-order systems of multidimension-valued memristive neural networks (FSMVMNNs) in this article. First, based on the comprehensive knowledge about mul...

Maximum A Posteriori Approximation of Hidden Markov Models for Proportional Sequential Data Modeling With Simultaneous Feature Selection.

IEEE transactions on neural networks and learning systems
One of the pillar generative machine learning approaches in time series data study and analysis is the hidden Markov model (HMM). Early research focused on the speech recognition application of the model with later expansion into numerous fields, inc...

Temporal Coding in Spiking Neural Networks With Alpha Synaptic Function: Learning With Backpropagation.

IEEE transactions on neural networks and learning systems
The timing of individual neuronal spikes is essential for biological brains to make fast responses to sensory stimuli. However, conventional artificial neural networks lack the intrinsic temporal coding ability present in biological networks. We prop...

Noise Robust Face Hallucination Based on Smooth Correntropy Representation.

IEEE transactions on neural networks and learning systems
Face hallucination technologies have been widely developed during the past decades, among which the sparse manifold learning (SML)-based approaches have become the popular ones and achieved promising performance. However, these SML methods always fai...

On the Rates of Convergence From Surrogate Risk Minimizers to the Bayes Optimal Classifier.

IEEE transactions on neural networks and learning systems
In classification, the use of 0-1 loss is preferable since the minimizer of 0-1 risk leads to the Bayes optimal classifier. However, due to the nonconvexity of 0-1 loss, this optimization problem is NP-hard. Therefore, many convex surrogate loss func...

Spherical Formation Tracking Control of Nonlinear Second-Order Agents With Adaptive Neural Flow Estimate.

IEEE transactions on neural networks and learning systems
This article addresses the spherical formation tracking control problem of nonlinear second-order vehicles moving in flowfields under both undirected networks and directed, strongly connected networks. Different from the previous adaptive estimate of...

Data-Driven Designs of Fault Detection Systems via Neural Network-Aided Learning.

IEEE transactions on neural networks and learning systems
With the aid of neural networks, this article develops two data-driven designs of fault detection (FD) for dynamic systems. The first neural network is constructed for generating residual signals in the so-called finite impulse response (FIR) filter-...

Degradation Alignment in Remaining Useful Life Prediction Using Deep Cycle-Consistent Learning.

IEEE transactions on neural networks and learning systems
Due to the benefits of reduced maintenance cost and increased operational safety, effective prognostic methods have always been highly demanded in real industries. In the recent years, intelligent data-driven remaining useful life (RUL) prediction ap...