AIMC Topic: Algorithms

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Semi-Supervised Deep Learning in High-Speed Railway Track Detection Based on Distributed Fiber Acoustic Sensing.

Sensors (Basel, Switzerland)
High deployment costs, safety risks, and time delays restrict traditional track detection methods in high-speed railways. Therefore, approaches based on optical sensors have become the most remarkable strategy in terms of deployment cost and real-tim...

Landscape Perception Identification and Classification Based on Electroencephalogram (EEG) Features.

International journal of environmental research and public health
This paper puts forward a new method of landscape recognition and evaluation by using aerial video and EEG technology. In this study, seven typical landscape types (forest, wetland, grassland, desert, water, farmland, and city) were selected. Differe...

A 1D CNN for high accuracy classification and transfer learning in motor imagery EEG-based brain-computer interface.

Journal of neural engineering
Brain-computer interface (BCI) aims to establish communication paths between the brain processes and external devices. Different methods have been used to extract human intentions from electroencephalography (EEG) recordings. Those based on motor ima...

Research on Artificial Intelligence Classification and Statistical Methods of Financial Data in Smart Cities.

Computational intelligence and neuroscience
In order to improve the effect of financial data classification and extract effective information from financial data, this paper improves the data mining algorithm, uses linear combination of principal components to represent missing variables, and ...

Attention based automated radiology report generation using CNN and LSTM.

PloS one
The automated generation of radiology reports provides X-rays and has tremendous potential to enhance the clinical diagnosis of diseases in patients. A new research direction is gaining increasing attention that involves the use of hybrid approaches ...

Fast and Accurate U-Net Model for Fetal Ultrasound Image Segmentation.

Ultrasonic imaging
U-Net based algorithms, due to their complex computations, include limitations when they are used in clinical devices. In this paper, we addressed this problem through a novel U-Net based architecture that called fast and accurate U-Net for medical i...

Deep learning versus iterative image reconstruction algorithm for head CT in trauma.

Emergency radiology
PURPOSE: To compare the image quality between a deep learning-based image reconstruction algorithm (DLIR) and an adaptive statistical iterative reconstruction algorithm (ASiR-V) in noncontrast trauma head CT.

ExAID: A multimodal explanation framework for computer-aided diagnosis of skin lesions.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: One principal impediment in the successful deployment of Artificial Intelligence (AI) based Computer-Aided Diagnosis (CAD) systems in everyday clinical workflows is their lack of transparent decision-making. Although common...

Bayesian-based optimized deep learning model to detect COVID-19 patients using chest X-ray image data.

Computers in biology and medicine
Coronavirus Disease 2019 (COVID-19) is extremely infectious and rapidly spreading around the globe. As a result, rapid and precise identification of COVID-19 patients is critical. Deep Learning has shown promising performance in a variety of domains ...

Towards Interpretable Machine Learning for Automated Damage Detection Based on Ultrasonic Guided Waves.

Sensors (Basel, Switzerland)
Data-driven analysis for damage assessment has a large potential in structural health monitoring (SHM) systems, where sensors are permanently attached to the structure, enabling continuous and frequent measurements. In this contribution, we propose a...