AIMC Topic: Algorithms

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A Vision-Based System for Stage Classification of Parkinsonian Gait Using Machine Learning and Synthetic Data.

Sensors (Basel, Switzerland)
Parkinson's disease is characterized by abnormal gait, which worsens as the condition progresses. Although several methods have been able to classify this feature through pose-estimation algorithms and machine-learning classifiers, few studies have b...

Polishing copy number variant calls on exome sequencing data via deep learning.

Genome research
Accurate and efficient detection of copy number variants (CNVs) is of critical importance owing to their significant association with complex genetic diseases. Although algorithms that use whole-genome sequencing (WGS) data provide stable results wit...

Design of Neural Network Model for Cross-Media Audio and Video Score Recognition Based on Convolutional Neural Network Model.

Computational intelligence and neuroscience
In this paper, the residual convolutional neural network is used to extract the note features in the music score image to solve the problem of model degradation; then, multiscale feature fusion is used to fuse the feature information of different lev...

Scene Classification in the Environmental Art Design by Using the Lightweight Deep Learning Model under the Background of Big Data.

Computational intelligence and neuroscience
On the basis of scene visual understanding technology, the research aims to further improve the classification efficiency and classification accuracy of art design scenes. The lightweight deep learning (DL) model based on big data is used as the main...

Artificial Intelligence-Based Semisupervised Self-Training Algorithm in Pathological Tissue Image Segmentation.

Computational intelligence and neuroscience
In the field of medical image processing, due to the differences in tissues, organs, and imaging methods, obtained medical images have significant differences. With the development of intelligence in medicine, an increasing number of computing optimi...

The Application of RBF Neural Network Model Based on Deep Learning for Flower Pattern Design in Art Teaching.

Computational intelligence and neuroscience
The rapid growth of artificial intelligence technology has been deployed in art teaching and learning. Radial basis function (RBF) networks have a completely different design compared to most neural network architectures. Most neural networks consist...

Hyperparameter Optimization of Bayesian Neural Network Using Bayesian Optimization and Intelligent Feature Engineering for Load Forecasting.

Sensors (Basel, Switzerland)
This paper proposes a new hybrid framework for short-term load forecasting (STLF) by combining the Feature Engineering (FE) and Bayesian Optimization (BO) algorithms with a Bayesian Neural Network (BNN). The FE module comprises feature selection and ...

A Novel Detection Refinement Technique for Accurate Identification of Burrows in Underwater Imagery.

Sensors (Basel, Switzerland)
With the evolution of the convolutional neural network (CNN), object detection in the underwater environment has gained a lot of attention. However, due to the complex nature of the underwater environment, generic CNN-based object detectors still fac...

A Primer into the Current State of Artificial Intelligence in Gastroenterology.

Journal of gastrointestinal and liver diseases : JGLD
Artificial intelligence (AI) is not a new idea or field of research. However, recent advancements in computing technology as well as increasing worldwide experience in applying AI to various fields have enabled us to hope that applying it to the medi...

Riemannian gradient methods for stochastic composition problems.

Neural networks : the official journal of the International Neural Network Society
In the paper, we study a class of novel stochastic composition optimization problems over Riemannian manifold, which have been raised by multiple emerging machine learning applications such as distributionally robust learning in Riemannian manifold s...