AIMC Topic: Algorithms

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A novel multi-branch architecture for state of the art robust detection of pathological phonocardiograms.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Heart auscultation is an inexpensive and fundamental technique to effectively diagnose cardiovascular disease. However, due to relatively high human error rates even when auscultation is performed by an experienced physician, and due to the not unive...

Advanced computation in cardiovascular physiology: new challenges and opportunities.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Recent developments in computational physiology have successfully exploited advanced signal processing and artificial intelligence tools for predicting or uncovering characteristic features of physiological and pathological states in humans. While th...

Chip Appearance Defect Recognition Based on Convolutional Neural Network.

Sensors (Basel, Switzerland)
To improve the recognition rate of chip appearance defects, an algorithm based on a convolution neural network is proposed to identify chip appearance defects of various shapes and features. Furthermore, to address the problems of long training time ...

Deep Convolutional Neural Network Optimization for Defect Detection in Fabric Inspection.

Sensors (Basel, Switzerland)
This research is aimed to detect defects on the surface of the fabric and deep learning model optimization. Since defect detection cannot effectively solve the fabric with complex background by image processing, this research uses deep learning to id...

Analysis of the Possibilities of Tire-Defect Inspection Based on Unsupervised Learning and Deep Learning.

Sensors (Basel, Switzerland)
At present, inspection systems process visual data captured by cameras, with deep learning approaches applied to detect defects. Defect detection results usually have an accuracy higher than 94%. Real-life applications, however, are not very common. ...

CMOS Implementation of ANNs Based on Analog Optimization of N-Dimensional Objective Functions.

Sensors (Basel, Switzerland)
The design of neural network architectures is carried out using methods that optimize a particular objective function, in which a point that minimizes the function is sought. In reported works, they only focused on software simulations or commercial ...

Intelligent Techniques for Detecting Network Attacks: Review and Research Directions.

Sensors (Basel, Switzerland)
The significant growth in the use of the Internet and the rapid development of network technologies are associated with an increased risk of network attacks. Network attacks refer to all types of unauthorized access to a network including any attempt...

Improve hot region prediction by analyzing different machine learning algorithms.

BMC bioinformatics
BACKGROUND: In the process of designing drugs and proteins, it is crucial to recognize hot regions in protein-protein interactions. Each hot region of protein-protein interaction is composed of at least three hot spots, which play an important role i...

Machine learning and chemometrics for electrochemical sensors: moving forward to the future of analytical chemistry.

The Analyst
Electrochemical sensors and biosensors have been successfully used in a wide range of applications, but systematic optimization and nonlinear relationships have been compromised for electrode fabrication and data analysis. Machine learning and experi...

Magnetic Resonance Image Feature Analysis under Deep Learning in Diagnosis of Neurological Rehabilitation in Patients with Cerebrovascular Diseases.

Contrast media & molecular imaging
To explore the impact of magnetic resonance imaging (MRI) image features based on deep learning algorithms on the neurological rehabilitation of patients with cerebrovascular diseases, eighty patients with acute cerebrovascular disease were selected ...