AIMC Topic: Neural Networks, Computer

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Construction and Application of Text Entity Relation Joint Extraction Model Based on Multi-Head Attention Neural Network.

Computational intelligence and neuroscience
Entity relationship extraction is one of the key areas of information extraction and is an important research content in the field of natural language processing. Based on past research, this paper proposes a combined extraction model based on a mult...

Network Anomaly Traffic Detection Algorithm Based on RIC-SC-DeCN.

Computational intelligence and neuroscience
In the research of network abnormal traffic detection, in view of the characteristics of high dimensionality and redundancy in traffic data and the loss of original information caused by the pooling operation in the convolutional neural network, whic...

Construction of Enterprise Financial Early Warning Model Based on Logistic Regression and BP Neural Network.

Computational intelligence and neuroscience
At present, the number of enterprises in financial crisis in China is rising sharply, and the ability of enterprises to resist risks is generally weak. Therefore, it is necessary to establish a corporate financial crisis early warning system, to dete...

Learning-based autonomous vascular guidewire navigation without human demonstration in the venous system of a porcine liver.

International journal of computer assisted radiology and surgery
PURPOSE: The navigation of endovascular guidewires is a dexterous task where physicians and patients can benefit from automation. Machine learning-based controllers are promising to help master this task. However, human-generated training data are sc...

Mandibular premolar identification system based on a deep learning model.

Journal of oral biosciences
OBJECTIVES: For constructing an isolated tooth identification system using deep learning, Igarashi et al. (2021) began constructing a learning model as basic research to identify the left and right mandibular first and second premolars. These teeth w...

A review on the application of deep learning for CT reconstruction, bone segmentation and surgical planning in oral and maxillofacial surgery.

Dento maxillo facial radiology
Computer-assisted surgery (CAS) allows clinicians to personalize treatments and surgical interventions and has therefore become an increasingly popular treatment modality in maxillofacial surgery. The current maxillofacial CAS consists of three main ...

YOLO-LOGO: A transformer-based YOLO segmentation model for breast mass detection and segmentation in digital mammograms.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Both mass detection and segmentation in digital mammograms play a crucial role in early breast cancer detection and treatment. Furthermore, clinical experience has shown that they are the upstream tasks of pathological class...

Rolling Bearing Fault Diagnosis Based on Markov Transition Field and Residual Network.

Sensors (Basel, Switzerland)
Data-driven rolling-bearing fault diagnosis methods are mostly based on deep-learning models, and their multilayer nonlinear mapping capability can improve the accuracy of intelligent fault diagnosis. However, problems such as gradient disappearance ...

Detecting Cyberattacks on Electrical Storage Systems through Neural Network Based Anomaly Detection Algorithm.

Sensors (Basel, Switzerland)
Distributed Energy Resources (DERs) are growing in importance Power Systems. Battery Electrical Storage Systems (BESS) represent fundamental tools in order to balance the unpredictable power production of some Renewable Energy Sources (RES). Neverthe...

A Deep Learning Method Approach for Sleep Stage Classification with EEG Spectrogram.

International journal of environmental research and public health
The classification of sleep stages is an important process. However, this process is time-consuming, subjective, and error-prone. Many automated classification methods use electroencephalogram (EEG) signals for classification. These methods do not cl...