AIMC Topic: Neural Networks, Computer

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Deepfake Detection Using the Rate of Change between Frames Based on Computer Vision.

Sensors (Basel, Switzerland)
Recently, artificial intelligence has been successfully used in fields, such as computer vision, voice, and big data analysis. However, various problems, such as security, privacy, and ethics, also occur owing to the development of artificial intelli...

Fault Detection in the MSW Incineration Process Using Stochastic Configuration Networks and Case-Based Reasoning.

Sensors (Basel, Switzerland)
Fault detection in the waste incineration process depends on high-temperature image observation and the experience of field maintenance personnel, which is inefficient and can easily cause misjudgment of the fault. In this paper, a fault detection me...

Multiple Damage Detection of an Offshore Helideck through the Two-Step Artificial Neural Network Based on the Limited Mode Shape Data.

Sensors (Basel, Switzerland)
A helideck is an essential structure in an offshore platform, and it is crucial to maintain its structural integrity and detect the occurrence of damage early. Because helidecks usually consist of complex lattice truss members, precise measurements a...

Coastal Image Classification and Pattern Recognition: Tairua Beach, New Zealand.

Sensors (Basel, Switzerland)
The study of coastal processes is critical for the protection and development of beach amenities, infrastructure, and properties. Many studies of beach evolution rely on data collected using remote sensing and show that beach evolution can be charact...

Spatio-temporal prediction of the COVID-19 pandemic in US counties: modeling with a deep LSTM neural network.

Scientific reports
Prediction of complex epidemiological systems such as COVID-19 is challenging on many grounds. Commonly used compartmental models struggle to handle an epidemiological process that evolves rapidly and is spatially heterogeneous. On the other hand, ma...

Deep learning is widely applicable to phenotyping embryonic development and disease.

Development (Cambridge, England)
Genome editing simplifies the generation of new animal models for congenital disorders. However, the detailed and unbiased phenotypic assessment of altered embryonic development remains a challenge. Here, we explore how deep learning (U-Net) can auto...

Multitask Healthcare Management Recommendation System Leveraging Knowledge Graph.

Journal of healthcare engineering
In this paper, a novel multitask healthcare management recommendation system leveraging the knowledge graph is proposed, which is based on deep neural network and 5G network, and it can be applied in mobile and terminal device to free up medical reso...

A Novel Context Aware Joint Segmentation and Classification Framework for Glaucoma Detection.

Computational and mathematical methods in medicine
Glaucoma is a chronic ocular disease characterized by damage to the optic nerve resulting in progressive and irreversible visual loss. Early detection and timely clinical interventions are critical in improving glaucoma-related outcomes. As a typical...

Single Shot Multibox Detector Automatic Polyp Detection Network Based on Gastrointestinal Endoscopic Images.

Computational and mathematical methods in medicine
PURPOSE: In order to resolve the situation of high missed diagnosis rate and high misdiagnosis rate of the pathological analysis of the gastrointestinal endoscopic images by experts, we propose an automatic polyp detection algorithm based on Single S...

Logistics Distribution Route Optimization Model Based on Recursive Fuzzy Neural Network Algorithm.

Computational intelligence and neuroscience
In recent years, more and more attention has been paid to the utilization of data and information in the logistics distribution path optimization system of e-commerce, but it is difficult to have scientific guarantee in the process of determining the...