AIMC Topic: Neural Networks, Computer

Clear Filters Showing 2141 to 2150 of 31376 articles

Electroencephalography Decoding with Conditional Identification Generator.

International journal of neural systems
Decoding Electroencephalography (EEG) signals are extremely useful for advancing and understanding human-artificial intelligence (AI) interaction systems. Recent advancements in deep neural networks (DNNs) have demonstrated significant promise in thi...

DeePMD-GNN: A DeePMD-kit Plugin for External Graph Neural Network Potentials.

Journal of chemical information and modeling
Machine learning potentials (MLPs) have revolutionized molecular simulation by providing efficient and accurate models for predicting atomic interactions. MLPs continue to advance and have had profound impact in applications that include drug discove...

Recent Advances in the Modeling of Ionic Liquids Using Artificial Neural Networks.

Journal of chemical information and modeling
This paper reviews the recent and most impactful advancements in the application of artificial neural networks in modeling the properties of ionic liquids. As salts that are liquid at temperatures below 100 °C, ionic liquids possess unique properties...

A comparative study of neuro-fuzzy and neural network models in predicting length of stay in university hospital.

BMC health services research
BACKGROUND: The time a patient spends in the hospital from admission to discharge is known as the length of stay (LOS). Predicting LOS is crucial for enhancing patient care, managing hospital resources, and optimizing the use of patient beds. Therefo...

Multimodal medical image fusion combining saliency perception and generative adversarial network.

Scientific reports
Multimodal medical image fusion is crucial for enhancing diagnostic accuracy by integrating complementary information from different imaging modalities. Current fusion techniques face challenges in effectively combining heterogeneous features while p...

Fall recognition using a three stream spatio temporal GCN model with adaptive feature aggregation.

Scientific reports
The prevention of falls is paramount in modern healthcare, particularly for the elderly, as falls can lead to severe injuries or even fatalities. Additionally, the growing incidence of falls among the elderly, coupled with the urgent need to prevent ...

Artificial intelligence for sustainable farming with dual branch convolutional graph attention networks in rice leaf disease detection.

Scientific reports
Rice is susceptible to various diseases, including brown spot, hispa, leaf smut, bacterial leaf blight, and leaf blast, all of which can negatively impact crop yields. Current disease detection methods encounter several challenges, such as reliance o...

Recurrent and convolutional neural networks in classification of EEG signal for guided imagery and mental workload detection.

Scientific reports
The Guided Imagery technique is reported to be used by therapists all over the world in order to increase the comfort of patients suffering from a variety of disorders from mental to oncology ones and proved to be successful in numerous of ways. Poss...

Early warning of deep coal miners' unsafe behavior based on the HFACS-CM-BP neural network.

International journal of occupational safety and ergonomics : JOSE
Preventing miners' unsafe behavior and reducing accidents in deep coal mines are crucial. This study comprehensively used methods such as the human factor analysis and classification system for China mines (HFACS-CM) model, grounded theory and the ba...

Robust one-class support vector machine.

Neural networks : the official journal of the International Neural Network Society
One-Class Support Vector Machine (OCSVM) is an effective algorithm in one-class classification task. However, it exhibits sensitivity to noise and outliers. Current solutions often employ bounded loss functions that impose finite but relatively large...