AIMC Topic: Neural Networks, Computer

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Hyperspectral Imaging for Mobile Robot Navigation.

Sensors (Basel, Switzerland)
The article presents the application of a hyperspectral camera in mobile robot navigation. Hyperspectral cameras are imaging systems that can capture a wide range of electromagnetic spectra. This feature allows them to detect a broader range of color...

A Study on Structural Health Monitoring of a Large Space Antenna via Distributed Sensors and Deep Learning.

Sensors (Basel, Switzerland)
Most modern Earth and Universe observation spacecraft are now equipped with large lightweight and flexible structures, such as antennas, telescopes, and extendable elements. The trend of hosting more complex and bigger appendages, essential for high-...

Study on an Assembly Prediction Method of RV Reducer Based on IGWO Algorithm and SVR Model.

Sensors (Basel, Switzerland)
This paper proposes a new method for predicting rotation error based on improved grey wolf-optimized support vector regression (IGWO-SVR), because the existing rotation error research methods cannot meet the production beat and product quality requir...

STC-NLSTMNet: An Improved Human Activity Recognition Method Using Convolutional Neural Network with NLSTM from WiFi CSI.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) has emerged as a significant area of research due to its numerous possible applications, including ambient assisted living, healthcare, abnormal behaviour detection, etc. Recently, HAR using WiFi channel state informa...

A Hybrid Model for Coronavirus Disease 2019 Forecasting Based on Ensemble Empirical Mode Decomposition and Deep Learning.

International journal of environmental research and public health
The novel coronavirus pneumonia that began to spread in 2019 is still raging and has placed a burden on medical systems and governments in various countries. For policymaking and medical resource decisions, a good prediction model is necessary to mon...

Efficient neural codes naturally emerge through gradient descent learning.

Nature communications
Human sensory systems are more sensitive to common features in the environment than uncommon features. For example, small deviations from the more frequently encountered horizontal orientations can be more easily detected than small deviations from t...

A study on pharmaceutical text relationship extraction based on heterogeneous graph neural networks.

Mathematical biosciences and engineering : MBE
Effective information extraction of pharmaceutical texts is of great significance for clinical research. The ancient Chinese medicine text has streamlined sentences and complex semantic relationships, and the textual relationships may exist between h...

NCSP-PLM: An ensemble learning framework for predicting non-classical secreted proteins based on protein language models and deep learning.

Mathematical biosciences and engineering : MBE
Non-classical secreted proteins (NCSPs) refer to a group of proteins that are located in the extracellular environment despite the absence of signal peptides and motifs. They usually play different roles in intercellular communication. Therefore, the...

Detection of microcalcifications in photon-counting dedicated breast-CT using a deep convolutional neural network: Proof of principle.

Clinical imaging
OBJECTIVE: In this study, we investigate the feasibility of a deep Convolutional Neural Network (dCNN), trained with mammographic images, to detect and classify microcalcifications (MC) in breast-CT (BCT) images.

Diagnosis of arrhythmias with few abnormal ECG samples using metric-based meta learning.

Computers in biology and medicine
A major challenge in artificial intelligence based ECG diagnosis lies that it is difficult to obtain sufficient annotated training samples for each rhythm type, especially for rare diseases, which makes many approaches fail to achieve the desired per...