AIMC Topic: Neural Networks, Computer

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Improving the Accuracy of an R-CNN-Based Crack Identification System Using Different Preprocessing Algorithms.

Sensors (Basel, Switzerland)
The accurate intelligent identification and detection of road cracks is a key issue in road maintenance, and it has become popular to perform this task through the field of computer vision. In this paper, we proposed a deep learning-based crack detec...

Blind Quality Prediction for View Synthesis Based on Heterogeneous Distortion Perception.

Sensors (Basel, Switzerland)
The quality of synthesized images directly affects the practical application of virtual view synthesis technology, which typically uses a depth-image-based rendering (DIBR) algorithm to generate a new viewpoint based on texture and depth images. Curr...

A Prediction Model of Defecation Based on BP Neural Network and Bowel Sound Signal Features.

Sensors (Basel, Switzerland)
(1) Background: Incontinence and its complications pose great difficulties in the care of the disabled. Currently, invasive incontinence monitoring methods are too invasive, expensive, and bulky to be widely used. Compared with previous methods, bowe...

Enhanced Convolutional Neural Network for In Situ AUV Thruster Health Monitoring Using Acoustic Signals.

Sensors (Basel, Switzerland)
As the demand for ocean exploration increases, studies are being actively conducted on autonomous underwater vehicles (AUVs) that can efficiently perform various missions. To successfully perform long-term, wide-ranging missions, it is necessary to a...

Deep Learning with LPC and Wavelet Algorithms for Driving Fault Diagnosis.

Sensors (Basel, Switzerland)
Vehicle fault detection and diagnosis (VFDD) along with predictive maintenance (PdM) are indispensable for early diagnosis in order to prevent severe accidents due to mechanical malfunction in urban environments. This paper proposes an early voicepri...

Aeroengine Working Condition Recognition Based on MsCNN-BiLSTM.

Sensors (Basel, Switzerland)
Aeroengine working condition recognition is a pivotal step in engine fault diagnosis. Currently, most research on aeroengine condition recognition focuses on the stable condition. To identify the aeroengine working conditions including transition con...

Graph Neural Network for Protein-Protein Interaction Prediction: A Comparative Study.

Molecules (Basel, Switzerland)
Proteins are the fundamental biological macromolecules which underline practically all biological activities. Protein-protein interactions (PPIs), as they are known, are how proteins interact with other proteins in their environment to perform biolog...

Survival Analysis with High-Dimensional Omics Data Using a Threshold Gradient Descent Regularization-Based Neural Network Approach.

Genes
Analysis of data with a censored survival response and high-dimensional omics measurements is now common. Most of the existing analyses are based on specific (semi)parametric models, in particular the Cox model. Such analyses may be limited by not ha...

Ransomware detection using deep learning based unsupervised feature extraction and a cost sensitive Pareto Ensemble classifier.

Scientific reports
Ransomware attacks pose a serious threat to Internet resources due to their far-reaching effects. It's Zero-day variants are even more hazardous, as less is known about them. In this regard, when used for ransomware attack detection, conventional mac...

Cultural Heritage Resource Development and Industrial Transformation Resource Value Assessment Based on BP Neural Network.

Computational intelligence and neuroscience
Mining and utilizing cultural heritage resources and creating and developing creative and cultural industries have become the priority direction of economic development, setting off a wave of cultural heritage resource development, and industrial tra...