AIMC Topic: Neural Networks, Computer

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Combining Knowledge Graph and Word Embeddings for Spherical Topic Modeling.

IEEE transactions on neural networks and learning systems
Probabilistic topic models are considered as an effective framework for text analysis that uncovers the main topics in an unlabeled set of documents. However, the inferred topics by traditional topic models are often unclear and not easy to interpret...

Spatial-Spectral Unified Adaptive Probability Graph Convolutional Networks for Hyperspectral Image Classification.

IEEE transactions on neural networks and learning systems
In hyperspectral image (HSI) classification task, semisupervised graph convolutional network (GCN)-based methods have received increasing attention. However, two problems still need to be addressed. The first is that the initial graph structure in th...

An Intelligent Method for Predicting the Pressure Coefficient Curve of Airfoil-Based Conditional Generative Adversarial Networks.

IEEE transactions on neural networks and learning systems
Recently, extensive studies have focused on analyzing aerodynamic performance due to its important impact on aircraft design. Most of these works compute the aerodynamic coefficient of the airfoil through computational fluid dynamics (CFD) simulation...

BayeSeg: Bayesian modeling for medical image segmentation with interpretable generalizability.

Medical image analysis
Due to the cross-domain distribution shift aroused from diverse medical imaging systems, many deep learning segmentation methods fail to perform well on unseen data, which limits their real-world applicability. Recent works have shown the benefits of...

Deep Learning-Based Skin Lesion Multi-class Classification with Global Average Pooling Improvement.

Journal of digital imaging
Cancerous skin lesions are one of the deadliest diseases that have the ability in spreading across other body parts and organs. Conventionally, visual inspection and biopsy methods are widely used to detect skin cancers. However, these methods have s...

Enhanced regularization for on-chip training using analog and temporary memory weights.

Neural networks : the official journal of the International Neural Network Society
In-memory computing techniques are used to accelerate artificial neural network (ANN) training and inference tasks. Memory technology and architectural innovations allow efficient matrix-vector multiplications, gradient calculations, and updates to n...

Evaluating the ecological vulnerability of Chongqing using deep learning.

Environmental science and pollution research international
This study used deep learning to evaluate the ecological vulnerability of Chongqing, China, discuss the deep learning evaluations of ecological vulnerability, and generate vulnerability maps that support local ecological environment protection and go...

Physically defined long-term and short-term synapses for the development of reconfigurable analog-type operators capable of performing health care tasks.

Science advances
Extracting valuable information from the overflowing data is a critical yet challenging task. Dealing with high volumes of biometric data, which are often unstructured, nonstatic, and ambiguous, requires extensive computer resources and data speciali...

A Probabilistic Digital Twin for Leak Localization in Water Distribution Networks Using Generative Deep Learning.

Sensors (Basel, Switzerland)
Localizing leakages in large water distribution systems is an important and ever-present problem. Due to the complexity originating from water pipeline networks, too few sensors, and noisy measurements, this is a highly challenging problem to solve. ...

Evaluation of 5G and Fixed-Satellite Service Earth Station (FSS-ES) Downlink Interference Based on Artificial Neural Network Learning Models (ANN-LMS).

Sensors (Basel, Switzerland)
Fifth-generation (5G) networks have been deployed alongside fourth-generation networks in high-traffic areas. The most recent 5G mobile communication access technology includes mmWave and sub-6 GHz C-bands. However, 5G signals possibly interfere with...