AIMC Topic: Neural Networks, Computer

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Diagnosing the Severity of Knee Osteoarthritis Using Regression Scores From Artificial Intelligence Convolution Neural Networks.

Orthopedics
BACKGROUND: This study focused on using deep learning neural networks to classify the severity of osteoarthritis in the knee. A continuous regression score of osteoarthritis severity has yet to be explored using artificial intelligence machine learni...

Deep learning approach for unified recognition of driver speed and lateral intentions using naturalistic driving data.

Neural networks : the official journal of the International Neural Network Society
Driver intention recognition is a critical component of advanced driver assistance systems, with significant implications for improving vehicle safety, intelligence, and fuel economy. However, previous research on driver intention recognition has not...

QCL Infrared Spectroscopy Combined with Machine Learning as a Useful Tool for Classifying Acetaminophen Tablets by Brand.

Molecules (Basel, Switzerland)
The development of new methods of identification of active pharmaceutical ingredients (API) is a subject of paramount importance for research centers, the pharmaceutical industry, and law enforcement agencies. Here, a system for identifying and class...

Research on the Influence of Information Iterative Propagation on Complex Network Structure.

Big data
Dynamic propagation will affect the change of network structure. Different networks are affected by the iterative propagation of information to different degrees. The iterative propagation of information in the network changes the connection strength...

Photonic deep residual time-delay reservoir computing.

Neural networks : the official journal of the International Neural Network Society
Time-delay reservoir computing (TDRC) represents a simplified variant of recurrent neural networks, employing a nonlinear node with a feedback mechanism to construct virtual nodes. The capabilities of TDRC can be enhanced by transitioning to a deep a...

Textual emotion classification using MPNet and cascading broad learning.

Neural networks : the official journal of the International Neural Network Society
As one of the most important tasks of natural language processing, textual emotion classification (TEC) aims to recognize and detect all emotions contained in texts. However, most existing methods are implemented using deep learning approaches, which...

An unsupervised multi-view contrastive learning framework with attention-based reranking strategy for entity alignment.

Neural networks : the official journal of the International Neural Network Society
Entity alignment is a crucial task in knowledge graphs, aiming to match corresponding entities from different knowledge graphs. Due to the scarcity of pre-aligned entities in real-world scenarios, research focused on unsupervised entity alignment has...

Prescribed performance adaptive neural event-triggered control for switched nonlinear cyber-physical systems under deception attacks.

Neural networks : the official journal of the International Neural Network Society
In this paper, the design of an adaptive neural event-triggered control scheme for a class of switched nonlinear systems affected by external disturbances and deception attacks is presented. In order to address the effects caused by unknown disturban...

AFFnet - a deep convolutional neural network for the detection of atypical femur fractures from anteriorposterior radiographs.

Bone
Despite well-defined criteria for radiographic diagnosis of atypical femur fractures (AFFs), missed and delayed diagnosis is common. An AFF diagnostic software could provide timely AFF detection to prevent progression of incomplete or development of ...

Skin cancer classification based on an optimized convolutional neural network and multicriteria decision-making.

Scientific reports
Skin cancer is a type of cancer disease in which abnormal alterations in skin characteristics can be detected. It can be treated if it is detected early. Many artificial intelligence-based models have been developed for skin cancer detection and clas...