AIMC Topic: Algorithms

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A Review of Computer Vision-Based Structural Deformation Monitoring in Field Environments.

Sensors (Basel, Switzerland)
Computer vision-based structural deformation monitoring techniques were studied in a large number of applications in the field of structural health monitoring (SHM). Numerous laboratory tests and short-term field applications contributed to the forma...

Research on Deep Learning Automatic Vehicle Recognition Algorithm Based on RES-YOLO Model.

Sensors (Basel, Switzerland)
With the introduction of concepts such as ubiquitous mapping, mapping-related technologies are gradually applied in autonomous driving and target recognition. There are many problems in vision measurement and remote sensing, such as difficulty in aut...

Machine Learning-Based Boosted Regression Ensemble Combined with Hyperparameter Tuning for Optimal Adaptive Learning.

Sensors (Basel, Switzerland)
Over the past couple of decades, many telecommunication industries have passed through the different facets of the digital revolution by integrating artificial intelligence (AI) techniques into the way they run and define their processes. Relevant da...

Probabilistic Seismic Response Prediction of Three-Dimensional Structures Based on Bayesian Convolutional Neural Network.

Sensors (Basel, Switzerland)
Seismic response prediction is a challenging problem and is significant in every stage during a structure's life cycle. Deep neural network has proven to be an efficient tool in the response prediction of structures. However, a conventional neural ne...

Predicting acute kidney injury following open partial nephrectomy treatment using SAT-pruned explainable machine learning model.

BMC medical informatics and decision making
BACKGROUND: One of the most prevalent complications of Partial Nephrectomy (PN) is Acute Kidney Injury (AKI), which could have a negative impact on subsequent renal function and occurs in up to 24.3% of patients undergoing PN. The aim of this study w...

End-to-end deep learning for interior tomography with low-dose x-ray CT.

Physics in medicine and biology
There are several x-ray computed tomography (CT) scanning strategies used to reduce radiation dose, such as (1) sparse-view CT, (2) low-dose CT and (3) region-of-interest (ROI) CT (called interior tomography). To further reduce the dose, sparse-view ...

Multimodal Feature Fusion Based Hypergraph Learning Model.

Computational intelligence and neuroscience
Hypergraph learning is a new research hotspot in the machine learning field. The performance of the hypergraph learning model depends on the quality of the hypergraph structure built by different feature extraction methods as well as its incidence ma...

Leak detection in real water distribution networks based on acoustic emission and machine learning.

Environmental technology
Water scarcity as well as social and economic damages caused by the increasing amounts of non-revenue water in the water distribution networks (WDNs) have been prompting innovative solutions. A great deal of potable water is wasted due to leakage in ...

Fast Analysis of Time-Domain Fluorescence Lifetime Imaging via Extreme Learning Machine.

Sensors (Basel, Switzerland)
We present a fast and accurate analytical method for fluorescence lifetime imaging microscopy (FLIM), using the extreme learning machine (ELM). We used extensive metrics to evaluate ELM and existing algorithms. First, we compared these algorithms usi...

Performance enhancement of an uncertain nonlinear medical robot with optimal nonlinear robust controller.

Computers in biology and medicine
Cardiopulmonary resuscitation refers to the process of sending oxygen and blood to the body's vital organs during cardiac arrest. For this reason, designing and controlling an accurate robot is crucial to saving the lives of patients. This study aims...