AIMC Topic: Neural Networks, Computer

Clear Filters Showing 16131 to 16140 of 31376 articles

EditPredict: Prediction of RNA editable sites with convolutional neural network.

Genomics
RNA editing exerts critical impacts on numerous biological processes. While millions of RNA editings have been identified in humans, much more are expected to be discovered. In this work, we constructed Convolutional Neural Network (CNN) models to pr...

Sex estimation from the greater sciatic notch: a comparison of classical statistical models and machine learning algorithms.

International journal of legal medicine
The greater sciatic notch (GSN) is a useful element for sex estimation because it is quite resistant to damage, and thus it can often be assessed even in poorly preserved skeletons. This study aimed to develop statistical models for sex estimation ba...

Targeted Free Energy Perturbation Revisited: Accurate Free Energies from Mapped Reference Potentials.

The journal of physical chemistry letters
We present an approach that extends the theory of targeted free energy perturbation (TFEP) to calculate free energy differences and free energy surfaces at an accurate quantum mechanical level of theory from a cheaper reference potential. The converg...

Enhancing 5G Small Cell Selection: A Neural Network and IoV-Based Approach.

Sensors (Basel, Switzerland)
The ultra-dense network (UDN) is one of the key technologies in fifth generation (5G) networks. It is used to enhance the system capacity issue by deploying small cells at high density. In 5G UDNs, the cell selection process requires high computation...

An Efficient CNN-Based Deep Learning Model to Detect Malware Attacks (CNN-DMA) in 5G-IoT Healthcare Applications.

Sensors (Basel, Switzerland)
The role of 5G-IoT has become indispensable in smart applications and it plays a crucial part in e-health applications. E-health applications require intelligent schemes and architectures to overcome the security threats against the sensitive data of...

A Method of CT Image Denoising Based on Residual Encoder-Decoder Network.

Journal of healthcare engineering
Low-dose computed tomography (CT) has proved effective in lowering radiation risk for the patients, but the resultant noise and bar artifacts in CT images can be a disturbance for medical diagnosis. The difficulty of modeling statistical features in ...

Medical Text Classification Using Hybrid Deep Learning Models with Multihead Attention.

Computational intelligence and neuroscience
To unlock information present in clinical description, automatic medical text classification is highly useful in the arena of natural language processing (NLP). For medical text classification tasks, machine learning techniques seem to be quite effec...

Leaf Recognition Based on Joint Learning Multiloss of Multimodel Convolutional Neural Networks: A Testing for Vietnamese Herb.

Computational intelligence and neuroscience
A new modification of multi-CNN ensemble training is investigated by combining multiloss functions from state-of-the-art deep CNN architectures for leaf image recognition. We first apply the U-Net model to segment leaf images from the background to i...

A Knowledge Graph Entity Disambiguation Method Based on Entity-Relationship Embedding and Graph Structure Embedding.

Computational intelligence and neuroscience
The purpose of knowledge graph entity disambiguation is to match the ambiguous entities to the corresponding entities in the knowledge graph. Current entity ambiguity elimination methods usually use the context information of the entity and its attri...

Neural networks for parameter estimation in microstructural MRI: Application to a diffusion-relaxation model of white matter.

NeuroImage
Specific features of white matter microstructure can be investigated by using biophysical models to interpret relaxation-diffusion MRI brain data. Although more intricate models have the potential to reveal more details of the tissue, they also incur...