AIMC Topic: Algorithms

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Beyond algorithms: The human touch machine-generated titles for enhancing click-through rates on social media.

PloS one
Artificial intelligence (AI) has the potential to revolutionize various domains by automating language-driven tasks. This study evaluates the effectiveness of an AI-assisted methodology, called the "POP Title AI Five-Step Optimization Method," in opt...

Deep demosaicking convolution neural network and quantum wavelet transform-based image denoising.

Network (Bristol, England)
Demosaicking is a popular scientific area that is being explored by a vast number of scientists. Current digital imaging technologies capture colour images with a single monochrome sensor. In addition, the colour images were captured using a sensor c...

External validation of an artificial intelligence model for Gleason grading of prostate cancer on prostatectomy specimens.

BJU international
OBJECTIVES: To externally validate the performance of the DeepDx Prostate artificial intelligence (AI) algorithm (Deep Bio Inc., Seoul, South Korea) for Gleason grading on whole-mount prostate histopathology, considering potential variations observed...

A novel approach for the effective prediction of cardiovascular disease using applied artificial intelligence techniques.

ESC heart failure
AIMS: The objective of this research is to develop an effective cardiovascular disease prediction framework using machine learning techniques and to achieve high accuracy for the prediction of cardiovascular disease.

Lag projective synchronization of discrete-time fractional-order quaternion-valued neural networks with time delays.

Neural networks : the official journal of the International Neural Network Society
This paper deals with the lag projective synchronization (LPS) problem for a class of discrete-time fractional-order quaternion-valued neural networks(DTFO QVNNs) systems with time delays. Firstly, a DTFOQVNNs system with time delay is constructed. S...

DPGCL: Dual pass filtering based graph contrastive learning.

Neural networks : the official journal of the International Neural Network Society
Graph Contrastive Learning (GCL), which learns node or graph representation from supervision signals derived from the graph data itself, has recently attracted extensive research attention and achieved great success. Remarkably, most of the existing ...

A collaborative neurodynamic approach with two-timescale projection neural networks designed via majorization-minimization for global optimization and distributed global optimization.

Neural networks : the official journal of the International Neural Network Society
In this paper, two two-timescale projection neural networks are proposed based on the majorization-minimization principle for nonconvex optimization and distributed nonconvex optimization. They are proved to be globally convergent to Karush-Kuhn-Tuck...

Deep network embedding with dimension selection.

Neural networks : the official journal of the International Neural Network Society
Network embedding is a general-purpose machine learning technique that converts network data from non-Euclidean space to Euclidean space, facilitating downstream analyses for the networks. However, existing embedding methods are often optimization-ba...

An informative dual ForkNet for video anomaly detection.

Neural networks : the official journal of the International Neural Network Society
An autoencoder for video anomaly detection task is a type of algorithm with the primary purpose of learning an "informative" representation of the normal data that can be used for identifying the abnormal data by learning to reconstruct a set of inpu...

Patient-ventilator asynchrony classification in mechanically ventilated patients: Model-based or machine learning method?

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Patient-ventilator asynchrony (PVA) is associated with poor clinical outcomes and remains under-monitored. Automated PVA detection would enable complete monitoring standard observational methods do not allow. While model-bas...