AIMC Topic: Neural Networks, Computer

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Overfitting One-Dimensional convolutional neural networks for Raman spectra identification.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Dedicated handheld spectrometers have been adopted by first responders and law enforcement agencies for in situ identification of unknown substances. Real-time spectral matching process is a pixel-by-pixel comparing of the unknown spectra with refere...

Granger causality test with nonlinear neural-network-based methods: Python package and simulation study.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Causality defined by Granger in 1969 is a widely used concept, particularly in neuroscience and economics. As there is an increasing interest in nonlinear causality research, a Python package with a neural-network-based caus...

Not every sample is efficient: Analogical generative adversarial network for unpaired image-to-image translation.

Neural networks : the official journal of the International Neural Network Society
Image translation is to learn an effective mapping function that aims to convert an image from a source domain to another target domain. With the proposal and further developments of generative adversarial networks (GANs), the generative models have ...

Signed network representation with novel node proximity evaluation.

Neural networks : the official journal of the International Neural Network Society
Currently, signed network representation has been applied to many fields, e.g., recommendation platforms. A mainstream paradigm of network representation is to map nodes onto a low-dimensional space, such that the node proximity of interest can be pr...

Weakly-supervised learning for catheter segmentation in 3D frustum ultrasound.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Accurate and efficient catheter segmentation in 3D ultrasound (US) is essential for ultrasound-guided cardiac interventions. State-of-the-art segmentation algorithms, based on convolutional neural networks (CNNs), suffer from high computational cost ...

MedGCN: Medication recommendation and lab test imputation via graph convolutional networks.

Journal of biomedical informatics
Laboratory testing and medication prescription are two of the most important routines in daily clinical practice. Developing an artificial intelligence system that can automatically make lab test imputations and medication recommendations can save co...

Brain tumor segmentation in MRI images using nonparametric localization and enhancement methods with U-net.

International journal of computer assisted radiology and surgery
PURPOSE: Segmentation is one of the critical steps in analyzing medical images since it provides meaningful information for the diagnosis, monitoring, and treatment of brain tumors. In recent years, several artificial intelligence-based systems have ...

Machine Learning Techniques for Increasing Efficiency of the Robot's Sensor and Control Information Processing.

Sensors (Basel, Switzerland)
Real-time systems are widely used in industry, including technological process control systems, industrial automation systems, SCADA systems, testing, and measuring equipment, and robotics. The efficiency of executing an intelligent robot's mission i...

LT-FS-ID: Log-Transformed Feature Learning and Feature-Scaling-Based Machine Learning Algorithms to Predict the -Barriers for Intrusion Detection Using Wireless Sensor Network.

Sensors (Basel, Switzerland)
The dramatic increase in the computational facilities integrated with the explainable machine learning algorithms allows us to do fast intrusion detection and prevention at border areas using Wireless Sensor Networks (WSNs). This study proposed a nov...

Propofol Anesthesia Depth Monitoring Based on Self-Attention and Residual Structure Convolutional Neural Network.

Computational and mathematical methods in medicine
METHODS: We compare nine index values, select CNN+EEG, which has good correlation with BIS index, as an anesthesia state observation index to identify the parameters of the model, and establish a model based on self-attention and dual resistructure c...