AIMC Topic: Algorithms

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Effects of Multi-Omics Characteristics on Identification of Driver Genes Using Machine Learning Algorithms.

Genes
Cancer is a complex disease caused by genomic and epigenetic alterations; hence, identifying meaningful cancer drivers is an important and challenging task. Most studies have detected cancer drivers with mutated traits, while few studies consider mul...

Seabed Modelling by Means of Airborne Laser Bathymetry Data and Imbalanced Learning for Offshore Mapping.

Sensors (Basel, Switzerland)
An important problem associated with the aerial mapping of the seabed is the precise classification of point clouds characterizing the water surface, bottom, and bottom objects. This study aimed to improve the accuracy of classification by addressing...

Prototype Regularized Manifold Regularization Technique for Semi-Supervised Online Extreme Learning Machine.

Sensors (Basel, Switzerland)
Data streaming applications such as the Internet of Things (IoT) require processing or predicting from sequential data from various sensors. However, most of the data are unlabeled, making applying fully supervised learning algorithms impossible. The...

Real-Time Sonar Fusion for Layered Navigation Controller.

Sensors (Basel, Switzerland)
Navigation in varied and dynamic indoor environments remains a complex task for autonomous mobile platforms. Especially when conditions worsen, typical sensor modalities may fail to operate optimally and subsequently provide inapt input for safe navi...

Application of unsupervised deep learning algorithms for identification of specific clusters of chronic cough patients from EMR data.

BMC bioinformatics
BACKGROUND: Chronic cough affects approximately 10% of adults. The lack of ICD codes for chronic cough makes it challenging to apply supervised learning methods to predict the characteristics of chronic cough patients, thereby requiring the identific...

Research on Intelligent Target Tracking Algorithm Based on MDNet under Artificial Intelligence.

Computational intelligence and neuroscience
Target tracking is an important subject in computer vision technology, which has developed rapidly in recent ten years, and its application have become wider and wider. In this process, it has transferred from a simple experimental tracking environme...

Machine learning models identify gene predictors of waggle dance behaviour in honeybees.

Molecular ecology resources
The molecular characterization of complex behaviours is a challenging task as a range of different factors are often involved to produce the observed phenotype. An established approach is to look at the overall levels of expression of brain genes-or ...

Assessment for Different Neural Networks with FeatureSelection in Classification Issue.

Sensors (Basel, Switzerland)
In general, the investigation of NN (neural network) computing systems requires the management of a significant number of simultaneous distinct algorithms, such as parallel computing, fault tolerance, classification, and data optimization. Supervised...

Aircraft Image Recognition Network Based on Hybrid Attention Mechanism.

Computational intelligence and neuroscience
With the deepening of deep learning research, progress has been made in artificial intelligence. In the process of aircraft classification, the precision rate of aircraft picture recognition based on traditional methods is low due to various types of...

Multisource Deep Transfer Learning Based on Balanced Distribution Adaptation.

Computational intelligence and neuroscience
The current traditional unsupervised transfer learning assumes that the sample is collected from a single domain. From the aspect of practical application, the sample from a single-source domain is often not enough. In most cases, we usually collect ...