AIMC Topic: Neural Networks, Computer

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Network Traffic Prediction Incorporating Prior Knowledge for an Intelligent Network.

Sensors (Basel, Switzerland)
Network traffic prediction is an important tool for the management and control of IoT, and timely and accurate traffic prediction models play a crucial role in improving the IoT service quality. The degree of burstiness in intelligent network traffic...

Deep Learning with Discriminative Margin Loss for Cross-Domain Consumer-to-Shop Clothes Retrieval.

Sensors (Basel, Switzerland)
Consumer-to-shop clothes retrieval refers to the problem of matching photos taken by customers with their counterparts in the shop. Due to some problems, such as a large number of clothing categories, different appearances of clothing items due to di...

Word Embedding Distribution Propagation Graph Network for Few-Shot Learning.

Sensors (Basel, Switzerland)
Few-shot learning (FSL) is of great significance to the field of machine learning. The ability to learn and generalize using a small number of samples is an obvious distinction between artificial intelligence and humans. In the FSL domain, most graph...

A Lightweight Convolutional Neural Network Model for Liver Segmentation in Medical Diagnosis.

Computational intelligence and neuroscience
Liver segmentation and recognition from computed tomography (CT) images is a warm topic in image processing which is helpful for doctors and practitioners. Currently, many deep learning methods are used for liver segmentation that takes a long time t...

Real-Time Tracking of Object Melting Based on Enhanced DeepLab 3+ Network.

Computational intelligence and neuroscience
In order to reveal the dissolution behavior of iron tailings in blast furnace slag, the main component of iron tailings, SiO, was used for research. Aiming at the problem of information loss and inaccurate extraction of tracking molten SiO particles ...

Unbalanced Fault Diagnosis Based on an Invariant Temporal-Spatial Attention Fusion Network.

Computational intelligence and neuroscience
The health status of mechanical bearings concerns the safety of equipment usage. Therefore, it is of crucial importance to monitor mechanical bearings. Currently, deep learning is the mainstream approach for this task. However, in practical situation...

Automated System for Identifying COVID-19 Infections in Computed Tomography Images Using Deep Learning Models.

Journal of healthcare engineering
Coronavirus disease 2019 (COVID-19) is a novel disease that affects healthcare on a global scale and cannot be ignored because of its high fatality rate. Computed tomography (CT) images are presently being employed to assist doctors in detecting COVI...

Towards understanding theoretical advantages of complex-reaction networks.

Neural networks : the official journal of the International Neural Network Society
Complex-valued neural networks have attracted increasing attention in recent years, while it remains open on the advantages of complex-valued neural networks in comparison with real-valued networks. This work takes one step on this direction by intro...

SSGraphCPI: A Novel Model for Predicting Compound-Protein Interactions Based on Deep Learning.

International journal of molecular sciences
Identifying compound-protein (drug-target, DTI) interactions (CPI) accurately is a key step in drug discovery. Including virtual screening and drug reuse, it can significantly reduce the time it takes to identify drug candidates and provide patients ...

Exploring Artificial Neural Networks Efficiency in Tiny Wearable Devices for Human Activity Recognition.

Sensors (Basel, Switzerland)
The increasing diffusion of tiny wearable devices and, at the same time, the advent of machine learning techniques that can perform sophisticated inference, represent a valuable opportunity for the development of pervasive computing applications. Mor...