AIMC Topic: Algorithms

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Fractional whale driving training-based optimization enabled transfer learning for detecting autism spectrum disorder.

Computational biology and chemistry
Autism Spectrum Disorder (ASD) is a neurological illness that degrades communication and interaction among others. Autism can be detected at any stage. Early detection of ASD is important in preventing the communication, interaction and behavioral ou...

Construction and verification of a machine learning-based prediction model of deep vein thrombosis formation after spinal surgery.

International journal of medical informatics
BACKGROUND: Deep vein thromboembolism (DVT) is a common postoperative complication with high morbidity and mortality rates. However, the safety and effectiveness of using prophylactic anticoagulants for preventing DVT after spinal surgery remain cont...

Image harmonization with Simple Hybrid CNN-Transformer Network.

Neural networks : the official journal of the International Neural Network Society
Image harmonization seeks to transfer the illumination distribution of the background to that of the foreground within a composite image. Existing methods lack the ability of establishing global-local pixel illumination dependencies between foregroun...

Relaxed stability criteria of delayed neural networks using delay-parameters-dependent slack matrices.

Neural networks : the official journal of the International Neural Network Society
This note aims to reduce the conservatism of stability criteria for neural networks with time-varying delay. To this goal, on the one hand, we construct an augmented Lyapunov-Krasovskii functional (LKF), incorporating some delay-product terms that ca...

Deep dual incomplete multi-view multi-label classification via label semantic-guided contrastive learning.

Neural networks : the official journal of the International Neural Network Society
Multi-view multi-label learning (MVML) aims to train a model that can explore the multi-view information of the input sample to obtain its accurate predictions of multiple labels. Unfortunately, a majority of existing MVML methods are based on the as...

Refining heart disease prediction accuracy using hybrid machine learning techniques with novel metaheuristic algorithms.

International journal of cardiology
Early diagnosis of heart disease is crucial, as it's one of the leading causes of death globally. Machine learning algorithms can be a powerful tool in achieving this goal. Therefore, this article aims to increase the accuracy of predicting heart dis...

Automated echocardiographic diastolic function grading: A hybrid multi-task deep learning and machine learning approach.

International journal of cardiology
BACKGROUND: Assessing left ventricular diastolic function (LVDF) with echocardiography as per ASE guidelines is tedious and time-consuming. The study aims to develop a fully automatic approach of this procedure by a lightweight hybrid algorithm combi...

Suitability of different machine learning algorithms for the classification of the proportion of grassland-based forages at the herd level using mid-infrared spectral information from routine milk control.

Journal of dairy science
As the call for an international standard for milk from grassland-based production systems continues to grow, so too do the monitoring and evaluation policies surrounding this topic. Individual stipulations by countries and milk producers to market t...

Machine vision-based detection of forbidden elements in the high-speed automatic scrap sorting line.

Waste management (New York, N.Y.)
Highly efficient industrial sorting lines require fast and reliable classification methods. Various types of sensors are used to measure the features of an object to determine which output class it belongs to. One technique involves the use of an RGB...

A Federated Learning Protocol for Spiking Neural Membrane Systems.

International journal of neural systems
Although deep learning models have shown promising results in solving problems related to image recognition or natural language processing, they do not match how the biological brain works. Some of the differences include the amount of energy consume...